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1
Emambakhsh, Mehryar. "Using the 3D shape of the nose for biometric authentication." Thesis, University of Bath, 2014. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.665386.
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This thesis is dedicated to exploring the potential of the 3D shape of the nasal region for face recognition. In comparison to other parts of the face, the nose has a number of distinctive features that make it attractive for recognition purposes. It is relatively stable over different facial expressions, easy to detect because of its salient convexity, and difficult to be intentionally cover up without attracting suspicion. In addition compared to other facial parts, such as forehead, chin, mouth and eyes, the nose is not vulnerable to unintentional occlusions caused by scarves or hair. Prior to undertaking a thorough analysis of the discriminative features of the 3D nasal regions, an overview of denoising algorithms and their impact on the 3D face recognition algorithms is first provided. This analysis, which is one of the first to address this issue, evaluates the performance of 3D holistic algorithms when various denoising methods are applied. One important outcome of this evaluation is to determine the optimal denoising parameters in terms of the overall 3D face recognition performance. A novel algorithm is also proposed to learn the statistics of the noise generated by the 3D laser scanners and then simulate it over the face point clouds. Using this process, the denoising and 3D face recognition algorithms’ robustness over various noise powers can be quantitatively evaluated. A new algorithm is proposed to find the nose tip from various expressions and self-occluded samples. Furthermore, novel applications of the nose region to align the faces in 3D is provided through two pose correction methods. The algorithms are very consistent and robust against different expressions, partial and self-occlusions. The nose’s discriminative strength for 3D face recognition is analysed using two approaches. The first one creates its feature sets by applying nasal curves to the depth map. The second approach utilises a novel feature space, based on histograms of normal vectors to the response of the Gabor wavelets applied to the nasal region. To create the feature spaces, various triangular and spherical patches and nasal curves are employed, giving a very high class separability. A genetic algorithm (GA) based feature selector is then used to make the feature space more robust against facial expressions. The basis of both algorithms is a highly consistent and accurate nasal region landmarking, which is quantitatively evaluated and compared with previous work. The recognition ranks provide the highest identification performance ever reported for the 3D nasal region. The results are not only higher than the previous 3D nose recognition algorithms, but also better than or very close to recent results for whole 3D face recognition. The algorithms have been evaluated on three widely used 3D face datasets, FRGC, Bosphorus and UMB-DB.
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Tambay, Alain Alimou. "Testing Fuzzy Extractors for Face Biometrics: Generating Deep Datasets." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41429.
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Biometrics can provide alternative methods for security than conventional authentication methods. There has been much research done in the field of biometrics, and efforts have been made to make them more easily usable in practice. The initial application for our work is a proof of concept for a system that would expedite some low-risk travellers’ arrival into the country while preserving the user’s privacy. This thesis focuses on the subset of problems related to the generation of cryptographic keys from noisy data, biometrics in our case.
This thesis was built in two parts. In the first, we implemented a key generating quantization-based fuzzy extractor scheme for facial feature biometrics based on the work by Dodis et al. and Sutcu, Li, and Memon. This scheme was modified to increased user privacy, address some implementation-based issues, and add testing-driven changes to tailor it towards its expected real-world usage. We show that our implementation does not significantly affect the scheme's performance, while providing additional protection against malicious actors that may gain access to the information stored on a server where biometric information is stored.
The second part consists of the creation of a process to automate the generation of deep datasets suitable for the testing of similar schemes. The process led to the creation of a larger dataset than those available for free online for minimal work, and showed that these datasets can be further expanded with only little additional effort. This larger dataset allowed for the creation of more representative recognition challenges. We were able to show that our implementation performed similarly to other non-commercial schemes. Further refinement will be necessary if this is to be compared to commercial applications.
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Aronsson, Erik. "Biometric Authentication and Penetration of Smartphones." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-37713.
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This study aims to examine the function and vulnerabilities of biometric systemsintegrated in smartphones, as well as techniques for circumventing the securityof these systems. These techniques are then used against a selection of smart-phones in order to gauge the resilience of their biometric security. The function,vulnerabilities, and techniques associated with these systems are compiled usinga literature study of published papers and books on the subject. The performedexperiments apply these techniques in the form of presentation attacks directed atthe fingerprint-, face- and iris recognition systems of the examined smartphones.The result of the experiments showed significant differences between the differentsmartphones, where some exhibited flawless security and others showed significantsecurity flaws. Both fingerprint and face recognition systems were successfullycircumvented, while none of the iris recognition systems were breached. No clearlink could be observed between the cost of the device and success rate of attacks,while only devices using the Android operating system were breached. The resultsundeniably showed that some smartphones are vulnerable to the employed tech-niques. It also showed that some of the tested devices had managed to implementmeasures to counteract the applied presentation attacks. The root cause of thevulnerabilities showcased in the experiment is due to the fact that biometric traitscan be copied and reproduced, highlighting a basic flaw of such systems.
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Porubsky, Jakub. "Biometric Authentication in M-Payments : Analysing and improving end-users’ acceptability." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-79221.
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Traditional authentication methods like Personal Identification Number (PIN) are getting obsolete and insecure for electronic-payments while mobile-payments are becoming more and more popular. Biometrics such as fingerprint and face recognition authentication methods seem to be a solution to this security issue as they are becoming a regular and integrated part of an average smartphone end-users purchase. However, for mobile-payments to be authenticated by biometrics, end-users acceptability of both technologies must be high. In this research, fingerprint and face recognition authentication methods are being tested with end-users and their current acceptability level is being determined based on interviews which are conducted upon finishing each testing scenario. The interview is using 39 questions which are determining previous usage of the technologies, their likeability, positives, negatives, and feelings about various features biometrics provide such as ease-of-use, stress-free method of payment, security, and many others. Additionally, one more authentication method is tested, namely two factor authentication consisting of one biometric method (fingerprint) and one traditional method (PIN) of authentication. The main goal for testing this method is to find out whether implementing (as currently it is not available) such technology into mobile-payments would be beneficial and how it scored in user-acceptance next to fingerprint and face recognition authentication methods. Once the user-acceptance level is determined the main reasons for it are presented. Last but not least, suggestions for improvements in this domain are presented so that biometrics are even more accepted by end-users who are performing mobile-payments on their smartphones.
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Bin, Mohd Isa Mohd Rizal. "Watermarked face recognition scheme : enhancing the security while maintaining the effectiveness of biometric authentication systems." Thesis, University of Portsmouth, 2016. https://researchportal.port.ac.uk/portal/en/theses/watermarked-face-recognition-scheme(a242609e-ba02-4cca-bfae-3615793fd018).html.
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Biometric authentication systems provide alternative solutions to traditional methods that are based on knowledge (e.g. password) or physical tokens (e.g., smart card). Many studies now focus on getting high accuracy rates for biometric verification. However,with advances in technology, biometric data (e.g. fingerprint, face, iris) can be captured/sniffed, duplicated, modified, and then resubmitted in the same or in other applications that utilize the same biometric features. Watermarking techniques can be used effectively to protect the genuine ownership of biometric data, either to accept or reject. This thesis presents a proposal for a suitable and viable combination of a face recognition algorithm and a watermarking technique, namely a Principal Component Analysis (PCA) and Discrete Cosine Transform (DCT) combination, that will ensure the authenticity of the data being transmitted in the face recognition system, which will then increase its level of security. The emphasis is on replay attack, which is recognizing and rejecting captured biometric data resubmitted into the system. The research begins with an analysis of biometric systems, with an emphasis on face recognition systems, and in particular with reference to the recorded threats on such systems. Biometric watermarking algorithms proposed by previous researchers within the face recognition environment are then studied, noting their proposed solutions to the said threats. This would then give a good idea towards a watermarking scheme to be proposed to enhance the security of face recognition systems, especially in terms of the authenticity of the data being transmitted. This proposed watermarking face recognition scheme is the main objective, which will be implemented in a PCA—DCT combination, followed by a check on all the 8 vulnerable positions where data may be captured and/or resubmitted. All the results produced are positive, apart from a few situations that will have to be left for future work. Non degradation of the individual PCA and DCT systems due to the combination is also checked and experimented on, again with positive results. Finally, the robustness of the watermarking scheme is experimented on to evaluate its resilience against attacks. The contributions from this research constitute a meaningful solution step to security problems associated with biometric techniques. The outcome of the research should also stimulate further research by opening up more research gaps in the area of combining biometric and watermarking techniques.
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Akalin, Volkan. "Face Recognition Using Eigenfaces And Neural Networks." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1055912/index.pdf.
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A face authentication system based on principal component analysis and neural networks is developed in this thesis. The system consists of three stagespreprocessing, principal component analysis, and recognition. In preprocessing stage, normalization illumination, and head orientation were done. Principal component analysis is applied to find the aspects of face which are important for identification. Eigenvectors and eigenfaces are calculated from the initial face image set. New faces are projected onto the space expanded by eigenfaces and represented by weighted sum of the eigenfaces. These weights are used to identify the faces. Neural network is used to create the face database and recognize and authenticate the face by using these weights. In this work, a separate network was build for each person. The input face is projected onto the eigenface space first and new descriptor is obtained. The new descriptor is used as input to each person&
#8217
s network, trained earlier. The one with maximum output is selected and reported as the host if it passes predefined recognition threshold. The algorithms that have been developed are tested on ORL, Yale and Feret Face Databases.
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Tan, Teewoon. "HUMAN FACE RECOGNITION BASED ON FRACTAL IMAGE CODING." University of Sydney. Electrical and Information Engineering, 2004. http://hdl.handle.net/2123/586.
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Human face recognition is an important area in the field of biometrics. It has been an active area of research for several decades, but still remains a challenging problem because of the complexity of the human face. In this thesis we describe fully automatic solutions that can locate faces and then perform identification and verification. We present a solution for face localisation using eye locations. We derive an efficient representation for the decision hyperplane of linear and nonlinear Support Vector Machines (SVMs). For this we introduce the novel concept of $\rho$ and $\eta$ prototypes. The standard formulation for the decision hyperplane is reformulated and expressed in terms of the two prototypes. Different kernels are treated separately to achieve further classification efficiency and to facilitate its adaptation to operate with the fast Fourier transform to achieve fast eye detection. Using the eye locations, we extract and normalise the face for size and in-plane rotations. Our method produces a more efficient representation of the SVM decision hyperplane than the well-known reduced set methods. As a result, our eye detection subsystem is faster and more accurate. The use of fractals and fractal image coding for object recognition has been proposed and used by others. Fractal codes have been used as features for recognition, but we need to take into account the distance between codes, and to ensure the continuity of the parameters of the code. We use a method based on fractal image coding for recognition, which we call the Fractal Neighbour Distance (FND). The FND relies on the Euclidean metric and the uniqueness of the attractor of a fractal code. An advantage of using the FND over fractal codes as features is that we do not have to worry about the uniqueness of, and distance between, codes. We only require the uniqueness of the attractor, which is already an implied property of a properly generated fractal code. Similar methods to the FND have been proposed by others, but what distinguishes our work from the rest is that we investigate the FND in greater detail and use our findings to improve the recognition rate. Our investigations reveal that the FND has some inherent invariance to translation, scale, rotation and changes to illumination. These invariances are image dependent and are affected by fractal encoding parameters. The parameters that have the greatest effect on recognition accuracy are the contrast scaling factor, luminance shift factor and the type of range block partitioning. The contrast scaling factor affect the convergence and eventual convergence rate of a fractal decoding process. We propose a novel method of controlling the convergence rate by altering the contrast scaling factor in a controlled manner, which has not been possible before. This helped us improve the recognition rate because under certain conditions better results are achievable from using a slower rate of convergence. We also investigate the effects of varying the luminance shift factor, and examine three different types of range block partitioning schemes. They are Quad-tree, HV and uniform partitioning. We performed experiments using various face datasets, and the results show that our method indeed performs better than many accepted methods such as eigenfaces. The experiments also show that the FND based classifier increases the separation between classes. The standard FND is further improved by incorporating the use of localised weights. A local search algorithm is introduced to find a best matching local feature using this locally weighted FND. The scores from a set of these locally weighted FND operations are then combined to obtain a global score, which is used as a measure of the similarity between two face images. Each local FND operation possesses the distortion invariant properties described above. Combined with the search procedure, the method has the potential to be invariant to a larger class of non-linear distortions. We also present a set of locally weighted FNDs that concentrate around the upper part of the face encompassing the eyes and nose. This design was motivated by the fact that the region around the eyes has more information for discrimination. Better performance is achieved by using different sets of weights for identification and verification. For facial verification, performance is further improved by using normalised scores and client specific thresholding. In this case, our results are competitive with current state-of-the-art methods, and in some cases outperform all those to which they were compared. For facial identification, under some conditions the weighted FND performs better than the standard FND. However, the weighted FND still has its short comings when some datasets are used, where its performance is not much better than the standard FND. To alleviate this problem we introduce a voting scheme that operates with normalised versions of the weighted FND. Although there are no improvements at lower matching ranks using this method, there are significant improvements for larger matching ranks. Our methods offer advantages over some well-accepted approaches such as eigenfaces, neural networks and those that use statistical learning theory. Some of the advantages are: new faces can be enrolled without re-training involving the whole database; faces can be removed from the database without the need for re-training; there are inherent invariances to face distortions; it is relatively simple to implement; and it is not model-based so there are no model parameters that need to be tweaked.
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Tan, Teewoon. "HUMAN FACE RECOGNITION BASED ON FRACTAL IMAGE CODING." Thesis, The University of Sydney, 2003. http://hdl.handle.net/2123/586.
Full textAbstract:
Human face recognition is an important area in the field of biometrics. It has been an active area of research for several decades, but still remains a challenging problem because of the complexity of the human face. In this thesis we describe fully automatic solutions that can locate faces and then perform identification and verification. We present a solution for face localisation using eye locations. We derive an efficient representation for the decision hyperplane of linear and nonlinear Support Vector Machines (SVMs). For this we introduce the novel concept of $\rho$ and $\eta$ prototypes. The standard formulation for the decision hyperplane is reformulated and expressed in terms of the two prototypes. Different kernels are treated separately to achieve further classification efficiency and to facilitate its adaptation to operate with the fast Fourier transform to achieve fast eye detection. Using the eye locations, we extract and normalise the face for size and in-plane rotations. Our method produces a more efficient representation of the SVM decision hyperplane than the well-known reduced set methods. As a result, our eye detection subsystem is faster and more accurate. The use of fractals and fractal image coding for object recognition has been proposed and used by others. Fractal codes have been used as features for recognition, but we need to take into account the distance between codes, and to ensure the continuity of the parameters of the code. We use a method based on fractal image coding for recognition, which we call the Fractal Neighbour Distance (FND). The FND relies on the Euclidean metric and the uniqueness of the attractor of a fractal code. An advantage of using the FND over fractal codes as features is that we do not have to worry about the uniqueness of, and distance between, codes. We only require the uniqueness of the attractor, which is already an implied property of a properly generated fractal code. Similar methods to the FND have been proposed by others, but what distinguishes our work from the rest is that we investigate the FND in greater detail and use our findings to improve the recognition rate. Our investigations reveal that the FND has some inherent invariance to translation, scale, rotation and changes to illumination. These invariances are image dependent and are affected by fractal encoding parameters. The parameters that have the greatest effect on recognition accuracy are the contrast scaling factor, luminance shift factor and the type of range block partitioning. The contrast scaling factor affect the convergence and eventual convergence rate of a fractal decoding process. We propose a novel method of controlling the convergence rate by altering the contrast scaling factor in a controlled manner, which has not been possible before. This helped us improve the recognition rate because under certain conditions better results are achievable from using a slower rate of convergence. We also investigate the effects of varying the luminance shift factor, and examine three different types of range block partitioning schemes. They are Quad-tree, HV and uniform partitioning. We performed experiments using various face datasets, and the results show that our method indeed performs better than many accepted methods such as eigenfaces. The experiments also show that the FND based classifier increases the separation between classes. The standard FND is further improved by incorporating the use of localised weights. A local search algorithm is introduced to find a best matching local feature using this locally weighted FND. The scores from a set of these locally weighted FND operations are then combined to obtain a global score, which is used as a measure of the similarity between two face images. Each local FND operation possesses the distortion invariant properties described above. Combined with the search procedure, the method has the potential to be invariant to a larger class of non-linear distortions. We also present a set of locally weighted FNDs that concentrate around the upper part of the face encompassing the eyes and nose. This design was motivated by the fact that the region around the eyes has more information for discrimination. Better performance is achieved by using different sets of weights for identification and verification. For facial verification, performance is further improved by using normalised scores and client specific thresholding. In this case, our results are competitive with current state-of-the-art methods, and in some cases outperform all those to which they were compared. For facial identification, under some conditions the weighted FND performs better than the standard FND. However, the weighted FND still has its short comings when some datasets are used, where its performance is not much better than the standard FND. To alleviate this problem we introduce a voting scheme that operates with normalised versions of the weighted FND. Although there are no improvements at lower matching ranks using this method, there are significant improvements for larger matching ranks. Our methods offer advantages over some well-accepted approaches such as eigenfaces, neural networks and those that use statistical learning theory. Some of the advantages are: new faces can be enrolled without re-training involving the whole database; faces can be removed from the database without the need for re-training; there are inherent invariances to face distortions; it is relatively simple to implement; and it is not model-based so there are no model parameters that need to be tweaked.
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Pereira, Tiago de Freitas 1985. "A comparative study of countermeasures to detect spoofing attacks in face authentication systems = Um estudo comparativo de contramedidas para detectar ataques de spoofing em sistemas de autenticação de faces." [s.n.], 2013. http://repositorio.unicamp.br/jspui/handle/REPOSIP/261478.
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Orientador: José Mario De MartinoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
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Marinho, Adriano da Silva. "Uma nova versão de um sistema de detecção e reconhecimento de face utilizando a Transformada Cosseno Discreta." Universidade Federal da Paraíba, 2012. http://tede.biblioteca.ufpb.br:8080/handle/tede/6088.
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Reliable identification systems have become key components in many applications that provide services to authenticated users. Since traditional authentication methods (such as using passwords or smartcards) can be manipulated in order to bypass the systems, biometric authentication methods have been receiving more attention in recent years. One of the biometric traits is the face. The problem of recognizing faces in video and photo still is an object of research, since there are many factors that influence the detection and recognition, such as lighting, position of the face, the background image, different facial expressions, etc. One can perform face recognition using Discrete Cosine Transform (DCT). In order to adjust a face recognition system to uncontrolled environments, two improvements for it were developed in this work: a image normalization module with respect to rotation and scale, and a change in the feature extraction module through the insertion of a non-ideal low-pass filter. The system and its modifications were tested on the following face databases: UFPB, ORL, Yale, and VSoft GTAV, developed specially for the job. Tests showed the efficiency of the image normalization module, but the system still is not adequate for every environment.
Sistemas de identificação confiáveis tornaram-se componentes chaves de várias aplicações que disponibilizam serviços para usuários autenticados. Uma vez que métodos de autenticação tradicionais (como os que utilizam senhas ou smartcards) podem ser manipulados com o objetivo de burlar os sistemas, métodos de autenticação biométrica vêm recebendo mais atenção nos últimos anos. Um dos traços biométricos é a face. O problema do reconhecimento de faces em vídeo e foto é objeto de pesquisa, uma vez que existem muitos fatores que influenciam na detecção e no reconhecimento, tais como: iluminação, posição da face, imagem ao fundo, diferentes expressões faciais, etc. É possível realizar reconhecimento facial utilizando a Transformada Cosseno Discreta (DCT). Com o intuito de adequar um Sistema de Detecção e Reconhecimento de Faces a ambientes não controlados, neste trabalho foram desenvolvidas duas melhorias para ele: um módulo normalizador de imagens em relação à rotação e à escala e uma modificação na etapa de seleção de atributos, por meio da inserção de um filtro passa-baixas não ideal. O sistema e suas modificações foram testados nos bancos de faces UFPB, ORL, Yale, GTAV e Vsoft, desenvolvido especialmente para o trabalho. Os testes mostraram a eficácia do módulo de normalização da imagem, mas ainda assim o sistema não é adequado para qualquer ambiente.
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Hariri, Walid. "Contribution à la reconnaissance/authentification de visages 2D/3D." Thesis, Cergy-Pontoise, 2017. http://www.theses.fr/2017CERG0905/document.
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L’analyse de visages 3D y compris la reconnaissance des visages et des expressions faciales 3D est devenue un domaine actif de recherche ces dernières années. Plusieurs méthodes ont été développées en utilisant des images 2D pour traiter ces problèmes. Cependant, ces méthodes présentent un certain nombre de limitations dépendantes à l’orientation du visage, à l’éclairage, à l’expression faciale, et aux occultations. Récemment, le développement des capteurs d’acquisition 3D a fait que les données 3D deviennent de plus en plus disponibles. Ces données 3D sont relativement invariables à l’illumination et à la pose, mais elles restent sensibles à la variation de l’expression. L’objectif principal de cette thèse est de proposer de nouvelles techniques de reconnaissance/vérification de visages et de reconnaissance d’expressions faciales 3D. Tout d’abord, une méthode de reconnaissance de visages en utilisant des matrices de covariance comme des descripteurs de régions de visages est proposée. Notre méthode comprend les étapes suivantes : le prétraitement et l’alignement de visages, un échantillonnage uniforme est ensuite appliqué sur la surface faciale pour localiser un ensemble de points de caractéristiques. Autours de chaque point, nous extrayons une matrice de covariance comme un descripteur de région du visage. Deux méthodes d’appariement sont ainsi proposées, et différentes distances (géodésiques / non-géodésique) sont appliquées pour comparer les visages. La méthode proposée est évaluée sur troisbases de visages GAVAB, FRGCv2 et BU-3DFE. Une description hiérarchique en utilisant trois niveaux de covariances est ensuite proposée et validée. La deuxième partie de cette thèse porte sur la reconnaissance des expressions faciales 3D. Pour ce faire, nous avons proposé d’utiliser les matrices de covariances avec les méthodes noyau. Dans cette contribution, nous avons appliqué le noyau de Gauss pour transformer les matrices de covariances en espace d’Hilbert. Cela permet d’utiliser les algorithmes qui sont déjà implémentés pour l’espace Euclidean (i.e. SVM) dans cet espace non-linéaire. Des expérimentations sont alors entreprises sur deux bases d’expressions faciales 3D (BU-3DFE et Bosphorus) pour reconnaître les six expressions faciales prototypiques3D face analysis including 3D face recognition and 3D Facial expression recognition has become a very active area of research in recent years. Various methods using 2D image analysis have been presented to tackle these problems. 2D image-based methods are inherently limited by variability in imaging factors such as illumination and pose. The recent development of 3D acquisition sensors has made 3D data more and more available. Such data is relatively invariant to illumination and pose, but it is still sensitive to expression variation. The principal objective of this thesis is to propose efficient methods for 3D face recognition/verification and 3D facial expression recognition. First, a new covariance based method for 3D face recognition is presented. Our method includes the following steps : first 3D facial surface is preprocessed and aligned. A uniform sampling is then applied to localize a set of feature points, around each point, we extract a matrix as local region descriptor. Two matching strategies are then proposed, and various distances (geodesic and non-geodesic) are applied to compare faces. The proposed method is assessed on three datasetsincluding GAVAB, FRGCv2 and BU-3DFE. A hierarchical description using three levels of covariances is then proposed and validated. In the second part of this thesis, we present an efficient approach for 3D facial expression recognition using kernel methods with covariance matrices. In this contribution, we propose to use Gaussian kernel which maps covariance matrices into a high dimensional Hilbert space. This enables to use conventional algorithms developed for Euclidean valued data such as SVM on such non-linear valued data. The proposed method have been assessed on two known datasets including BU-3DFE and Bosphorus datasets to recognize the six prototypical expressions
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Рижова, А. С. "Інформаційно-екстремальний метод аутентифікації користувача за фотографією обличчя." Thesis, Сумський державний університет, 2014. http://essuir.sumdu.edu.ua/handle/123456789/39146.
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У сучасному інформаційному суспільстві збільшується сегмент систем людино-машинної взаємодії на базі інтелектуальних компонентів. Серед задач, що вирішують ці компоненти, варто виділити персоналізацію та аутентифікацію користувача інформаційних баз чи соціальних сервісів, які перспективно вирішувати на базі вбудованих відеокамер через їх поширеність в складі мобільних пристроїв.
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Дмитерко, Василь Миколайович, and Vasyl Dmyterko. "дослідження систем підтримки прийняття рішень в біометричних системах аутентифікації." Thesis, Тернопільський національний технічний університет імені Івана Пулюя, 2017. http://elartu.tntu.edu.ua/handle/123456789/19006.
Full textAbstract:
Дипломна робота присвячена дослідженню систем підтримки прийняття рішень в біометричних системах аутентифікації.
Удосконалення полягає у розробці способу виділення біометричних параметрів на основі контрольних точок обличчя. Також виконано огляд основних принципів та методів біометричної аутентифікації та ідентифікації, огляд біометричних способів аутентифікації людини за рисами обличчя, а також наведено відомості про існуючі системи ідентифікації та програми для аутентифікації по обличчю. Було досліджено зразки у вигляді цифрових фото людини та на їх основі розроблено спосіб виділення біометричних ознак.The improvement is in the development of an allocation method for biometric parameters that are based on the face control points. It was also reviewed some basic principles and methods of biometric authentication and identification, biometric methods of human authentication by facial features, and it was provided the information about the existing identification systems and face authentication software. The digital photo samples of a person were studied and the biometric features selection method was developed based on those samples.
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Penteado, Bruno Elias [UNESP]. "Autenticação biométrica de usuários em sistemas de E-learning baseada em reconhecimento de faces a partir de vídeo." Universidade Estadual Paulista (UNESP), 2009. http://hdl.handle.net/11449/98692.
Full textAbstract:
Made available in DSpace on 2014-06-11T19:29:40Z (GMT). No. of bitstreams: 0
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penteado_be_me_sjrp.pdf: 1032009 bytes, checksum: 4cf143854132e42249128674b69ba77b (MD5)Nos últimos anos tem sido observado um crescimento exponencial na oferta de cursos a distância realizados pela Internet, decorrente de suas vantagens e características (menores custos de distribuição e atualização de conteúdo, gerenciamento de grandes turmas, aprendizado assíncrono e geograficamente independente, etc.), bem como de sua regulamentação e apoio governamental. Entretanto, a falta de mecanismos eficazes para assegurar a autenticação dos alunos neste tipo de ambiente é apontada como uma séria deficiência, tanto no acesso ao sistema quanto durante a participação do usuário nas atividades do curso. Atualmente, a autenticação baseada em senhas continua predominante. Porém, estudos têm sido conduzidos sobre possíveis aplicações da Biometria para autenticação em ambientes Web. Com a popularização e conseqüente barateamento de hardware habilitado para coleta biométrica (como webcams, microfone e leitores de impressão digital embutidos), a Biometria passa a ser considerada uma forma segura e viável de autenticação remota de indivíduos em aplicações Web. Baseado nisso, este trabalho propõe uma arquitetura distribuída para um ambiente de e-Learning, explorando as propriedades de um sistema Web para a autenticação biométrica tanto no acesso ao sistema quanto de forma contínua, durante a realização do curso. Para análise desta arquitetura, é avaliada a performance de técnicas de reconhecimento de faces a partir de vídeo capturadas on-line por uma webcam em um ambiente de Internet, simulando a interação natural de um indivíduo em um sistema de e- Learning. Para este fim, foi criada uma base de dados de vídeos própria, contando com 43 indivíduos navegando e interagindo com páginas Web. Os resultados obtidos mostram que os métodos analisados, consolidados na literatura, podem ser aplicados com sucesso nesse tipo de aplicação...
In the last years it has been observed an exponential growth in the offering of Internet-enabled distance courses, due to its advantages and features (decreased distribution and content updates costs, management of large groups of students, asynchronous and geographically independent learning) as well as its regulation and governmental support. However, the lack of effective mechanisms that assure user authentication in this sort of environment has been pointed out as a serious deficiency, both in the system logon and during user attendance in the course assignments. Currently, password based authentication still prevails. Nevertheless, studies have been carried out about possible biometric applications for Web authentication. With the popularization and resultant decreasing costs of biometric enabled devices, such as webcams, microphones and embedded fingerprint sensors, Biometrics is reconsidered as a secure and viable form of remote authentication of individuals for Web applications. Based on that, this work presents a distributed architecture for an e-Learning environment, by exploring the properties of a Web system for biometric authentication both in the system logon and in continuous monitoring, during the course attendance. For the analysis of this architecture, the performance of techniques for face recognition from video, captured on-line by a webcam in an Internet environment, is evaluated, simulating the natural interaction of an individual in an e-Learning system. For that, a private database was created, with 43 individuals browsing and interacting with Web pages. The results show that the methods analyzed, though consolidated in the literature, can be successfully applied in this kind of application, with recognition rates up to 97% in ideal conditions, with low execution times and with short amount of information transmitted between client and server, with templates sizes of about 30KB.
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Penteado, Bruno Elias. "Autenticação biométrica de usuários em sistemas de E-learning baseada em reconhecimento de faces a partir de vídeo /." São José do Rio Preto : [s.n.], 2009. http://hdl.handle.net/11449/98692.
Full textAbstract:
Orientador: Aparecido Nilceu EliasBanca: Agma Juci Machado Traina
Banca: Wilson Massashiro Yonezawa
Resumo: Nos últimos anos tem sido observado um crescimento exponencial na oferta de cursos a distância realizados pela Internet, decorrente de suas vantagens e características (menores custos de distribuição e atualização de conteúdo, gerenciamento de grandes turmas, aprendizado assíncrono e geograficamente independente, etc.), bem como de sua regulamentação e apoio governamental. Entretanto, a falta de mecanismos eficazes para assegurar a autenticação dos alunos neste tipo de ambiente é apontada como uma séria deficiência, tanto no acesso ao sistema quanto durante a participação do usuário nas atividades do curso. Atualmente, a autenticação baseada em senhas continua predominante. Porém, estudos têm sido conduzidos sobre possíveis aplicações da Biometria para autenticação em ambientes Web. Com a popularização e conseqüente barateamento de hardware habilitado para coleta biométrica (como webcams, microfone e leitores de impressão digital embutidos), a Biometria passa a ser considerada uma forma segura e viável de autenticação remota de indivíduos em aplicações Web. Baseado nisso, este trabalho propõe uma arquitetura distribuída para um ambiente de e-Learning, explorando as propriedades de um sistema Web para a autenticação biométrica tanto no acesso ao sistema quanto de forma contínua, durante a realização do curso. Para análise desta arquitetura, é avaliada a performance de técnicas de reconhecimento de faces a partir de vídeo capturadas on-line por uma webcam em um ambiente de Internet, simulando a interação natural de um indivíduo em um sistema de e- Learning. Para este fim, foi criada uma base de dados de vídeos própria, contando com 43 indivíduos navegando e interagindo com páginas Web. Os resultados obtidos mostram que os métodos analisados, consolidados na literatura, podem ser aplicados com sucesso nesse tipo de aplicação... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: In the last years it has been observed an exponential growth in the offering of Internet-enabled distance courses, due to its advantages and features (decreased distribution and content updates costs, management of large groups of students, asynchronous and geographically independent learning) as well as its regulation and governmental support. However, the lack of effective mechanisms that assure user authentication in this sort of environment has been pointed out as a serious deficiency, both in the system logon and during user attendance in the course assignments. Currently, password based authentication still prevails. Nevertheless, studies have been carried out about possible biometric applications for Web authentication. With the popularization and resultant decreasing costs of biometric enabled devices, such as webcams, microphones and embedded fingerprint sensors, Biometrics is reconsidered as a secure and viable form of remote authentication of individuals for Web applications. Based on that, this work presents a distributed architecture for an e-Learning environment, by exploring the properties of a Web system for biometric authentication both in the system logon and in continuous monitoring, during the course attendance. For the analysis of this architecture, the performance of techniques for face recognition from video, captured on-line by a webcam in an Internet environment, is evaluated, simulating the natural interaction of an individual in an e-Learning system. For that, a private database was created, with 43 individuals browsing and interacting with Web pages. The results show that the methods analyzed, though consolidated in the literature, can be successfully applied in this kind of application, with recognition rates up to 97% in ideal conditions, with low execution times and with short amount of information transmitted between client and server, with templates sizes of about 30KB.
Mestre
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Yadav, Tarun Kumar. "Automatic Detection and Prevention of Fake Key Attacks in Signal." BYU ScholarsArchive, 2019. https://scholarsarchive.byu.edu/etd/9072.
Full textAbstract:
The Signal protocol provides end-to-end encryption for billions of users in popular instant messaging applications like WhatsApp, Facebook Messenger, and Google Allo. The protocol relies on an app-specific central server to distribute public keys and relay encrypted messages between the users. Signal prevents passive attacks. However, it is vulnerable to some active attacks due to its reliance on a trusted key server. A malicious key server can distribute fake keys to users to perform man-in-the-middle or impersonation attacks. Signal applications support an authentication ceremony to detect these active attacks. However, this places an undue burden on the users to manually verify each other's public key. Recent studies reveal that the authentication ceremony is time-consuming and confusing, and almost nobody adopts it. Our goal is to explore various approaches for automatically detecting or preventing fake key attacks. We modified a local copy of the Signal server to demonstrate that active attacks are feasible. We then designed three defenses that automatically detect or prevent the attacks. We completed a threat analysis of the defenses and implemented some proof-of-concept prototypes for two of them. We analyze their strengths and weaknesses and outline avenues for future work.
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Murphy, Caroline (Caroline Elizabeth). "Fact and sanctity : authenticating laudianism in the English Monasticon anglicanum's architectural prints (1655)." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/106421.
Full textAbstract:
Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2016.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 111-119).
This thesis takes as its focus the set of illustrated plates of monastic churches and cathedrals that interleave the first volume of the Monasticon Anglicanun, a monumental Latin antiquarian tome on England's dissolved monastic establishments published in 1655. It was arranged by the antiquaries William Dugdale and Roger Dodsworth from compiled transcriptions of monastic foundation charters, and was illustrated in the early 1650s by the engraver Daniel King with over fifty full-page plates of dissolved monastic churches and cathedrals. The etcher Wenceslaus Hollar also contributed a few etchings to the project. The ambitions of this antiquarian endeavor were articulated in the publication's preface. The Monasticon was to preserve a memory of the institutional histories of monasteries, which had been dissolved and dismantled by Henry VIII's administration at the outset of the Reformation in the 1530s and 1540s, and attacked again by iconoclasts during the early years of the Civil War in the 1640s. A second objective was to record the appearances of monastic churches and cathedrals that had been converted for Protestant worship during the monastic dissolutions, and were thus among the few medieval religious structures to have weathered the iconoclastic storms largely intact. In the Monasticon, however, antiquarian desires to preserve were also underpinned by the political ambitions of its royalist, Laudian creators and benefactors to authenticate their conservative vision of the Church of England at a time when they faced persecution under Oliver Cromwell's republican regime. This thesis examines how the illustrated plates in the Monasticon's first volume depict dissolved monastic churches and cathedrals to advance and justify the aims of embattled Laudian royalists. By analyzing the graphic construction of these pictures in relation to seventeenth-century antiquarian practices and Laudian religious beliefs, these representations emerge as complex visual statements that stage monastic churches and cathedrals simultaneously as factual, historical antiquities, and also as sanctified religious spaces. Moreover, as a series of prints, these images form a collection of "paper monuments" that are recruited as artifactual evidence in support of a historical narrative that seeks to legitimize a Laudian vision of the Church, by demonstrating that it had deep roots in England's past. This thesis interrogates a set of compelling, yet overlooked antiquarian representations to open a window onto the complex and entangled meanings that were ascribed to medieval religious architecture after the Reformation, and in so doing it aligns with a growing body of scholarship that seeks to question the Weberian notion that this religious revolution heralded the "disenchantment of the world."
by Caroline Murphy.
S.M.
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Tai, Chiu-Yuan, and 戴久芫. "Anti-cheat methods for face authentication system spoofed by high resolution fake face." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/jxte5t.
Full textAbstract:
碩士亞東技術學院
資訊與通訊工程研究所
103
Due to the multiple convenient qualities (quick, remote detection ability, non-contact), face detection has been widely applied in fields such as access control, monitoring, auto focusing systems, or verification of the subject’s identity and behavior. However, with the widespread adoption of face detection technique, spoofing technique had become increasingly advanced with face Information being forged or collected to deceive or bypass the verification of face detection system. Thus, it is crucial for the biometric system to identify the forged characteristics. In this thesis, three fake face detection strategies based on analyzing characteristics of high-definition display, including the brightness of face image, DCT component of face edge, and hue of face image, are proposed to detect the capturing images. By using a PNN model to establish the image analysis system, the system can effectively identify fake face images from the input sequences. Moreover, to reduce the error probability from a single shut, sequence analysis method is also proposed to improve the system identification correctness, thus increase the stability and practicability of the proposed system.
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Chen, Ke-Zhao, and 陳科兆. "Video-based Face Authentication Using Appearance Models." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/63184216675446029330.
Full textAbstract:
碩士國立中正大學
資訊工程所
93
In this thesis, we present a novel face authentication scheme by using appearance models and Hidden Markov Models. In our face authentication system, it can be roughly divided into two parts. First, the appearance model is used for features extraction, because an appearance model can not only extract the texture information, but also extract the shape information. We consider the shape information of a face is useful for the face authentication. Thus, we train an appearance model with a training set of labeled image sequences and then use this model to extract the low dimensional features of every image. In order to construct a face authentication system, we apply a vector quantization scheme to classify these features and combine the HMM to make full use of the temporal information across the video sequences. After all parameters in HMM are calculated, we can determine the thresholds dynamically for face authentication. An iterative algorithm with these thresholds is also proposed to select a suitable state number in HMM and a suitable class number of observations, because the performance of face authentication is affected by both variables. As the result of experiment, we can show that our proposed video-based face authentication system works well on our constructed database. This database contains sixty-four video face sequences for training and sixty-four video face sequences for testing.
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HUANG, YU-TING, and 黃毓庭. "Rapid Identity Authentication System Based On Face Recognition." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/00756799098747815028.
Full textAbstract:
碩士國立臺北教育大學
資訊科學系碩士班
105
As scientific technology has continuously improved and developed, rapidity and accuracy has become the basic and essential features of biometric identification. There are many different kinds of methods to deal with objects comparison in biometric identification. For instance, shape detection and edge detection are both commonly used in biometric identification. However, face recognition is a typically integrated application of image analysis, image decomposition and classification. While the face is the most complex biological feature which the widest varieties of analysis are needed, the current solution to this is mostly to find stable reference points for objects comparison. Therefore, the purpose of this study is to explore the methods of face recognition and improve its response time of the recognition system. The images taken by webcams and the Internet environment of the users which have been enable the user to do the face detection via Internet websites. Furthermore, those records of the user’s frontal face have been provided further face recognition for identification system. The above is that the research question wants to be discussed and solved. The experiment of face recognition in this paper has been conducted through Binary Two Dimensional Principal Component Analysis (B2DPCA). Moreover, the experiment has been done with two different network environment and six different situations. The results have shown that the methods in our study effectively accelerate the rate of face recognition and assist the teachers in having better control of the attendance rate while the face recognition has been applied in online course attendance system.
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Yang, Cheng-Wei, and 楊政偉. "Local Transform Features and Hybridization for Face Authentication." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/52555783961692864689.
Full textAbstract:
碩士國立中央大學
資訊工程學系在職專班
104
In the digital era, we have to identify everyone to protect individual rights and information for bureau of entry and exit, network transactions, entry access control at home or corporate, etc. Traditional identity authentication methods have been insufficient for our needs, for example ID card, seal certification, etc. Currently, biometric technology is the most convenient and secure way on fingerprint authentication, face authentication, retina authentication, etc. In biometrics, face authentication not only has the highest acceptance of general public, but also the wide range of applications. It has three advantages 1) no need to touch 2) does not require user involvement or cooperation 3) the biometric collection process will not have any discomfort. Therefore, we propose the novel local transform feature: local gradient patterns (LGP) [1] and hybridization feature [1] that combines LBP, LGP by means of the AdaBoost method in face authentication (face verification). It will transform the face images into the LGP, and hybridization feature images. Then face authentication model was trained base on feature images and AdaBoost algorithm. LGP will calculate the neighboring gradient of a given pixel and its average of neighboring gradient. Then the average of neighboring gradient was set to center pixel. If neighboring gradient is greater than center pixel, LGP assigns one and zero otherwise which makes the local intensity variations along the edge components robust. According to the best local transform feature having the lowest classification error, LBP and LGP feature are fused by AdaBoost for hybridization of local transform features. This hybridization makes face detection performance robust to changes in global illumination by LBP, local intensity changes by LGP. In the actual experiments, we utilize a different number of positive samples and negative samples training face authentication model and the accuracy under various sample numbers are demonstrated. In addition, CMU PIE database is applied in our experiments. Experimental results show that our LGP and hybridization could improve accuracy and reduce the risk of counterfeit identity in terms of face authentication.
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Tseng, Tz-Chia, and 曾子家. "Anti-Spoofing of Live Face Authentication on Smartphone." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/7j6fm5.
Full textAbstract:
碩士國立臺灣大學
生醫電子與資訊學研究所
107
Our proposed method is capable of authenticating the input image is from real user or spoofing attack, including paper photograph, digital photograph, and video, using only the Red, Green, Blue (RGB) frontal camera of common smart phone, without the help of depth camera or infrared thermal sensor. We first capture live faces in each frame of input video streams by single shot multi-box detector then feed into our designed convolution neural network after certain data augmentation and finally obtain a well-trained spoof face classifier.
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"Face authentication on mobile devices: optimization techniques and applications." 2005. http://library.cuhk.edu.hk/record=b5892581.
Full textAbstract:
Pun Kwok Ho.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 106-111).
Abstracts in English and Chinese.
Chapter 1. --- Introduction --- p.1
Chapter 1.1 --- Background --- p.1
Chapter 1.1.1 --- Introduction to Biometrics --- p.1
Chapter 1.1.2 --- Face Recognition in General --- p.2
Chapter 1.1.3 --- Typical Face Recognition Systems --- p.4
Chapter 1.1.4 --- Face Database and Evaluation Protocol --- p.5
Chapter 1.1.5 --- Evaluation Metrics --- p.7
Chapter 1.1.6 --- Characteristics of Mobile Devices --- p.10
Chapter 1.2 --- Motivation and Objectives --- p.12
Chapter 1.3 --- Major Contributions --- p.13
Chapter 1.3.1 --- Optimization Framework --- p.13
Chapter 1.3.2 --- Real Time Principal Component Analysis --- p.14
Chapter 1.3.3 --- Real Time Elastic Bunch Graph Matching --- p.14
Chapter 1.4 --- Thesis Organization --- p.15
Chapter 2. --- Related Work --- p.16
Chapter 2.1 --- Face Recognition for Desktop Computers --- p.16
Chapter 2.1.1 --- Global Feature Based Systems --- p.16
Chapter 2.1.2 --- Local Feature Based Systems --- p.18
Chapter 2.1.3 --- Commercial Systems --- p.20
Chapter 2.2 --- Biometrics on Mobile Devices --- p.22
Chapter 3. --- Optimization Framework --- p.24
Chapter 3.1 --- Introduction --- p.24
Chapter 3.2 --- Levels of Optimization --- p.25
Chapter 3.2.1 --- Algorithm Level --- p.25
Chapter 3.2.2 --- Code Level --- p.26
Chapter 3.2.3 --- Instruction Level --- p.27
Chapter 3.2.4 --- Architecture Level --- p.28
Chapter 3.3 --- General Optimization Workflow --- p.29
Chapter 3.4 --- Summary --- p.31
Chapter 4. --- Real Time Principal Component Analysis --- p.32
Chapter 4.1 --- Introduction --- p.32
Chapter 4.2 --- System Overview --- p.33
Chapter 4.2.1 --- Image Preprocessing --- p.33
Chapter 4.2.2 --- PCA Subspace Training --- p.34
Chapter 4.2.3 --- PCA Subspace Projection --- p.36
Chapter 4.2.4 --- Template Matching --- p.36
Chapter 4.3 --- Optimization using Fixed-point Arithmetic --- p.37
Chapter 4.3.1 --- Profiling Analysis --- p.37
Chapter 4.3.2 --- Fixed-point Representation --- p.38
Chapter 4.3.3 --- Range Estimation --- p.39
Chapter 4.3.4 --- Code Conversion --- p.42
Chapter 4.4 --- Experiments and Discussions --- p.43
Chapter 4.4.1 --- Experiment Setup --- p.43
Chapter 4.4.2 --- Execution Time --- p.44
Chapter 4.4.3 --- Space Requirement --- p.45
Chapter 4.4.4 --- Verification Accuracy --- p.45
Chapter 5. --- Real Time Elastic Bunch Graph Matching --- p.49
Chapter 5.1 --- Introduction --- p.49
Chapter 5.2 --- System Overview --- p.50
Chapter 5.2.1 --- Image Preprocessing --- p.50
Chapter 5.2.2 --- Landmark Localization --- p.51
Chapter 5.2.3 --- Feature Extraction --- p.52
Chapter 5.2.4 --- Template Matching --- p.53
Chapter 5.3 --- Optimization Overview --- p.54
Chapter 5.3.1 --- Computation Optimization --- p.55
Chapter 5.3.2 --- Memory Optimization --- p.56
Chapter 5.4 --- Optimization Strategies --- p.58
Chapter 5.4.1 --- Fixed-point Arithmetic --- p.60
Chapter 5.4.2 --- Gabor Masks and Bunch Graphs Precomputation --- p.66
Chapter 5.4.3 --- Improving Array Access Efficiency using ID array --- p.68
Chapter 5.4.4 --- Efficient Gabor Filter Selection --- p.75
Chapter 5.4.5 --- Fine Tuning System Cache Policy --- p.79
Chapter 5.4.6 --- Reducing Redundant Memory Access by Loop Merging --- p.80
Chapter 5.4.7 --- Maximizing Cache Reuse by Array Merging --- p.90
Chapter 5.4.8 --- Optimization of Trigonometric Functions using Table Lookup. --- p.97
Chapter 5.5 --- Summary --- p.99
Chapter 6. --- Conclusions --- p.103
Chapter 7. --- Bibliography --- p.106
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Van, der Haar Dustin Terence. "Face recognition-based authentication and monitoring in video telecommunication systems." Thesis, 2012. http://hdl.handle.net/10210/5024.
Full textAbstract:
M.Sc. (Computer Science)A video conference is an interactive meeting between two or more locations, facilitated by simultaneous two-way video and audio transmissions. People in a video conference, also known as participants, join these video conferences for business and recreational purposes. In a typical video conference, we should properly identify and authenticate every participant in the video conference, if information discussed during the video conference is confidential. This prevents unauthorized and unwanted people from being part of the conference and exposing any confidential information during the video conference. Present existing video conferencing systems however, have problems in this area, resulting in some risks. These risks relate precisely to the lack of facilities to properly identify and authenticate participants, making it possible for unwanted/unauthorised participants to join the conference or masquerade as another participant. It is especially a problem, when facilitators or organisers are the only participants that know the authorised participants, or participants allowed in a video conference. In this dissertation, we review the risks that are present in video conferencing, and create a security system, (called BioVid) that mitigates the identification and authentication risks in video conferences. BioVid uses a Speeded-Up Robust Features or SURF-based face recognition approach, to identify and authenticate any participant in a video conference. BioVid continuously monitors the participants to check if masquerading has occurred and when it does detect an unauthorised participant, it informs the Service Provider. The Service Provider can then deal with the problem by either kicking the participant or asking the other participants to vote the unauthorised participant out of the video conference.
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Ayyagari, Venkat Rao. "Post invariant 3D face authentication based on Gaussian fields approach." 2005. http://etd.utk.edu/2005/AyyagariVenkat.pdf.
Full textAbstract:
Thesis (M.S.) -- University of Tennessee, Knoxville, 2005.Title from title page screen (viewed on January 30, 2006). Thesis advisor: Mongi A. Abidi. Document formatted into pages (xiii, 110 p. : ill. (some col.)). Vita. Includes bibliographical references (p. 103-109).
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li-Yu-Sin and 李鈺新. "Real-time Face Recognition for Multi-user Authentication on Smartphones." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/qkbktj.
Full text
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Cho, Chien-Lung, and 卓建隆. "Authentication of Biosignal Transmission Based on Face Recognition for Telemedicine." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/03211355438242624239.
Full textAbstract:
碩士國立臺灣大學
電機工程學研究所
94
Telemedicine has been defined as the use of telecommunications to provide medical information and services. By the transmission of electronic signals from one site to another, people can have the same medical care as that in hospital. Recently with the advancement of internet technology, the telemedicine is more convenient and acceptable to people. Although telemedicine makes long-distance medical services possible, it is not completely suitable to each user. As result of the internet security, telemedicine must have complicated procedures of authentications to prevent user’s privacy from losing. But these complex operations maybe block some people, especially to people with disabilities. So how we can improve these? We propose a new approach to replace traditional authentications in telemedicine. This new approach is face recognition being one of the biometric authentications. Substituting face recognition for manual input will decrease the difficulties in telemedicine. We hope it can provide users with a more convenient and well operational environment.
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Wang, Ying-Yu, and 王穎宇. "Parallel-AdaBoost Blink Detection for Live Face Recognition Authentication Systemand Its Embedded 4-Factor Authentication System Implementation." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/3t77ru.
Full textAbstract:
碩士國立雲林科技大學
電機工程系
102
Conventional face recognition authentication system is unable to discriminate real-world human faces from faces in the photo or in the video, and is easily faked by faces in the photo or in the video. So live face recognition authentication system with accurate live detection is getting fundamental and crucial. In order to accomplish real-time live face recognition authentication system, live detection based on blink detection and some extra simple live motion analysis is a cost-effective and high-practicability auxiliary method, especially the blink detection is the most intuitive and noninvasive. This thesis proposes Parallel-AdaBoost blink detection to perform AdaBoost eyes detection stage and AdaBoost open-eyes detection stage simultaneously through multithreaded parallelism. That is, AdaBoost open-eyes detection works on the region of interest of eyes candidate detected by AdaBoost eyes detection simultaneously and iteratively. If the detection result of AdaBoost open-eyes detection is true, the eyes are open. If otherwise, the eyes are half-closed or completely-closed. Live blink motion is determined by two alternatively-happened detection results of AdaBoost open-eyes detection. Experimental results show the detection accuracy and execution speed of proposed Parallel-AdaBoost blink detection are better than conventional ones. The proposed Parallel-AdaBoost blink detection can prevent face recognition authentication system from being broken by faces in the photo, and some extra simple live motion request and analysis can be integrated to further prevent face recognition authentication system from being cheated by faces in the video. On the other hand, on Android embedded platform, this thesis implements and integrates the proposed Parallel-AdaBoost blink detection to accomplish “Portable 4-Factor Authentication Device Accelerated By Multi-Thread Pipeline Parallelism” for applications of mobile payment, mobile authentication, and mobile locker.
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Hsin-TingWu and 吳欣庭. "Increasing Pairs of Makeup and Non-makeup Face Dataset Using Face Authentication Based on Partial Least Squares." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/92235854203608376554.
Full text
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Chang, Yea-Hsin, and 張逸昕. "Analyzing the Product Development and Competition Strategy of Microsoft Face Authentication Feature." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/80891614323304750428.
Full textAbstract:
碩士國立臺灣大學
資訊管理學研究所
104
Microsoft Face Authentication is a new feature of Windows 10, Human’s unique face pattern can be used as a digital certificate, be as an alternative solution of password, in order to sign-in protected systems. By comparing with previous OS version, it brings up product differentiation to users, and may activate their upgrade motivation. Furthermore, this feature works with cloud services by two-factor authentication, is another security enhancement feature. Face Authentication is required to work with specific IR camera design, therefore the marketing share of IR camera modules can represent the scale-out status of the feature. Microsoft expects that Face Authentication will create synergy with Windows 10 product marketing image. However, the marketing share is less than 1% in Windows launch anniversary. The combination of Value Net study shows the path of Microsoft, Module Makers, OEMs and end-users went non-efficiently; the high cost of module causes slow production, and OEMs are hesitated for the feature adoption. To enable IR camera module and Face Authentication ecosystem, by security and accuracy quality bar remaining high, it is possible to extend the marketing share by cost redundant, where the specification of hardware requirement be leveraged by reasonable adjustment, like far distance, FOV, ambient light bar, etc. When the switching costs are acceptable from RGB camera to RGB-IR camera, it is easier to scale-out the Face Authentication module adoption and win the market in the future.
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Chang, Hung-tu, and 張宏圖. "Automatic Energy Saving and Security Authentication Using Real-Time Face Detection and Verification." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/14983995469443652707.
Full textAbstract:
碩士國立中央大學
資訊工程學系碩士在職專班
100
In this thesis, an automatic energy saving and security authentication device using real-time face detection and verification is presented. Traditional consumer electronics devices do not have real-time auto shut-off function when users leave or forget to turn off the machine. It consequently results in energy wasting and the threat to security and confidentiality. Although nuclear power is cheap and high-efficiency, it will seriously endanger human health and environment once pollution occurs. To achieve the goals of energy-saving, carbon reduction, and environmental protection and secrecy, we propose a device using real-time face detection and verification to automatically turn off the monitor while human is absent. It will also authenticate the identity of human when the human present in front of the monitor again to determine whether to turn on the monitor or not. In the proposed system, the presented face is detected first and then use Principal Component Analysis (PCA) to extract face features to form face feature vector and decrease the dimensionality of face feature vectors thereafter. Finally, k-th nearest neighbor (KNN) method is employed to find the nearest face candidate. If this face has been authenticated, the monitor will be automatically turn on. If the user leave out of sight, the monitor will be automatically turn off so as to reduce the waste of power consumption while increasing the security and confidentiality of the users. Experimental results demonstrate that 93% accuracy rate of face detection can be attained. The accuracy rate of face verification of user is 93%. The accuracy rate of face verification of non-user is 87%. Experimental results reveal the feasibility and validity of the proposed mechanism in real-time energy saving while enhancing the security and confidentiality of the users.
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Lu, Shey-Shin, and 呂學信. "Study on the Face Membership Authentication Based on the Combination of SVDD and SVM Classifiers." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/09626081612779891343.
Full textAbstract:
碩士中原大學
機械工程研究所
95
Owing to the urgent demand of the security system in recent year, the technology related to identity authentication using biometrics has received much attention. Biometrics such as retina, fingerprint, voiceprint and human face of every individual are unique and exclusive. Among these natures, facial feature-based recognition is one of the most straightforward and feasible ways to develop identity authentication systems. For face membership authentication systems, the challenge is how to collect numerous data for the training process, especially the unknown nonmember set. In addition, the construction of the decision hyperplane to accurately classify the unseen nonmember patterns remains difficult. This thesis proposes a new classifier which combines both one-class and binary classification strategies. The principal component analysis (PCA) is utilized to extract the most discriminating features and reduce the dimensionality of input training data first, then employ the support vector data description (SVDD) to map the member data to high dimensional feature space. Then, a spherical decision boundary is learned to exclude most nonmembers. Furthermore, support vector machines (SVM) is used to construct an optimal separating hyperplane (OSH) to distinguish the members and those few nonmembers inside the hypersphere. By using the fusion strategy, the proposed classifier outperforms others, such as SVM, ISVM (Imbalanced SVM), SVM ensemble, SVDD, when faced with nonmembers that are not included in the training. The results also indicate that the proposed classifier is able to gain better stability and generalization performance for face membership authentication.
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Sueng, Chien-Cheng, and 宋健誠. "Fast Stretching Homomorphic Filter for Illumination/Shadow/Contrast Normalizationand Its Android Face Recognition Authentication Implementation." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/55794412803474638309.
Full textAbstract:
碩士國立雲林科技大學
電機工程系碩士班
100
The accuracy of face recognition system is inevitably error-prone to environmental interference, like illumination, light color, and shadow. So illumination/shadow/contrast normalization is the key point to the reliability of face recognition system. This thesis proposes a simple but practical method for illumination/shadow/contrast normalization, and improves face recognition system’s robustness to environmental illumination, irregular shadow, and light color variation. In order to achieve all normalization of illumination, shadow, and contrast, this thesis reviews pros and cons of conventional methods, like histogram equalization, local binary pattern, and fast Homomorphic filter, and proposes a illumination/shadow/contrast normalization method, fast stretching Homomorphic filter. The proposed method is divided into two main steps. The first step is to normalize the illumination and shadow through fast Homomorphic filter, and the second step is to compress the contrast of the overall image through illumination stretching normalization and to enhance the contrast of regions of interest on human face simultaneously. Finally, the proposed fast stretching Homomorphic filter for illumination/shadow/contrast normalization is implemented and integrated on portable Android face recognition authentication system so as to accomplish mobile payment devices featuring 3-factor authentication and resisting various environmental interference.
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Liao, Wei-Hsiang, and 廖偉翔. "Distance Transform and Circle Matching for Precise Eye Detectionand Its Android Face Recognition Authentication Implementation." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/83036549079565357934.
Full textAbstract:
碩士國立雲林科技大學
電機工程系碩士班
100
In face recognition system, eye coordinate localized by the step of eye detection is the key information foundation to the steps of pose normalization, geometry normalization, and illumination/shadow/contrast normalization. Once the steps of pose normalization, geometry normalization, and illumination/shadow/contrast normalization work well, the variation of pose, geometry, and illumination among human faces can be suppressed, and the subsequent steps of feature extraction and feature matching can have an objective and fair basis. However, most conventional eye detection methods simply can localize the eye candidate roughly so that the process of the pose normalization, geometry normalization, and illumination/shadow/contrast normalization is nothing but coarse. Therefore, based on the eye own circle feature and the strong black/white contrast, this thesis propose a precise eye detection method, distance transform and circle matching. That is, it applies the circle matching method to calibrate the referenced eye coordinate evaluated by the distance transform method. In the proposed method, at first, the distance transform method evaluates the referenced eye coordinate from the eye candidate image localized by AdaBoost eye detection method. Then, in the intersected image of edge images of the eye candidate image and its binary image, some circle-feature edges are preserved and the circle matching method is performed to seek and choose top five circle (center, radius, etc.) candidates. Finally, top five circle candidates are matched with the area of the binary image of the eye candidate image and the best matched one is picked up to localize the eye coordinate precisely. In contrast to conventional eye detection methods, the proposed method can localize the eye coordinate more accurately and reliably, and can overcome the difficulties of the environmental interference, like reflection damage, eyelid occlusion, or eye tail shadow. Finally, the proposed distance transform and circle matching for precise eye detection is implemented and integrated on portable Android face recognition authentication system so as to accomplish mobile payment devices featuring 3-factor authentication and resisting various environmental interference.
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Chang, Ming-Yuan, and 張銘元. "An Automatic Management System for Human Face Recognition and Authentication Based on Intuitive and Conditional Facial Feature Comparison." Thesis, 2001. http://ndltd.ncl.edu.tw/handle/24291076573205876199.
Full textAbstract:
碩士靜宜大學
資訊管理學系
89
Due to the wide applications of digital information, the usage of digital images is dramatically increased. If we can extract more valuable information from digital images, images will be getting more important. We try to count the number of human faces in a given image. And using this technology, image information can be converted into more valuable information to support decision-making process. In the first step, this paper will focus on the application of counting the number of human faces in a given digital image. By observation, we have found that the human faces have some crucial characteristics, and these characteristics could be collected together to build a rule database. And the database can be used to make the examination of a given image more efficient. It is useful to detect human faces in a normal picture, even if the background of the picture is complex. Moreover, these rules could be changed based on different application environments and needs. Next, we study the problems of human face recognition. Based on our observations, the human vision always recognizes the differences among faces via some feature conditions. We will propose an intuitive method to simulate the human vision in the human face recognition processing. Through comparing with the conditions of facial feature points, the proposed method can exactly and promptly identify each and every one human being in a digital image automatically. In other words, a fully automatically human recognition system will be implemented. The research result of this paper will be very practical. Through the images captured by video cameras, our systems will generate valuable information hidden in the images, which can be used as reference of other application. We can apply our results on Automatic Teller Machines (ATMS) and security systems to prevent illegal access.
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Seidlová, Tereza. "Vybrané problémy českých médií a novinářské profese na příkladu pronikání smyšlených událostí a recesistických obsahů do zpravodajství." Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-330484.
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This diploma thesis focuses on the problematic aspects of the journalistic profession nowadays, namely on the example of the penetration of the mystifying jokes to the mainstream media. In three specific cases where the authors of the mystifying pranks managed to penetrate the media, the work illustrates the most common mistakes journalists can make and focuses on trends, which stand for these tendencies. Part of this work is the analysis of the mystifying contents that appeared on jokes websites, on Facebook or in the context of interpersonal communication, and subsequent analysis of the media in which these mystifying reports appeared in the form of the real events. The interviews with both stakeholders - authors of the hoax contents and media representatives - will subsequently serve for the illustration of the overall issue and the final conclusion.
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Silva, Henrique Joaquim Duarte da. "Uma solução de handover seguro com QoS em redes veiculares." Master's thesis, 2013. http://hdl.handle.net/1822/29435.
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Dissertação de mestrado integrado em Engenharia de ComunicaçõesAs redes veiculares surgiram como um caso particular de redes ad hoc móveis denominadas por MANETS (Mobile Ad-hoc Networks), formando um campo específico de pesquisa na área de redes de computadores. As VANETs, (Vehicular Ad-hoc Networks) têm sido alvo de várias pesquisas científicas para o desenvolvimento do Sistema Inteligente de Transporte, sendo agora possível incluir nos automóveis software inteligente que melhorara a qualidade de vida dos condutores, através por exemplo de aplicações de entretenimento das quais se destaca a aplicação VoIP (Voice Over Internet Protocol). Neste tipo de redes, devido à elevada mobilidade dos veículos ocorre a perda de conectividade entre dispositivos, essa perda de conectividade deve-se ao facto de um dispositivo móvel trocar de rede, a este processo dá-se o nome de handover. Constituindo o handover um grave problema nas redes veiculares, principalmente aquando da utilização de aplicações tempo-real como é o caso da aplicação VoIP, é relevante desenvolver mecanismos que melhore a gestão do handover. Neste trabalho é apresentada uma solução que corresponde à execução de uma fase de pré-registo. Esta solução foi desenvolvida no sentido de se alcançar um handover seguro e com qualidade de serviço. Relativamente à segurança esta solução baseia-se no protocolo SIP (Session Initiation Protocol) e possibilita a utilização de um mecanismo de autenticação mútua através de troca de chaves. Quanto à qualidade de serviço a solução permite diminuir substancialmente o número de handovers, tendo a velocidade dos veículos e o número de RSUs (Road Side Units) espalhados pela estrada um papel preponderante na análise da mesma. Pela simulação realizada, através dos resultados obtidos foi possível verificar a eficiência desta solução para a obtenção de um handover seguro e com qualidade de serviço.
Vehicular networks have emerged as a particular case of mobile ad hoc networks called for MANETs (Mobile Ad-hoc Networks) forming a specific investigation field of computer networks. The VANETs (Vehicular Ad-hoc Networks) has been the subject of several scientific researches for the development of Intelligent Transportation Systems. Now its possible to include intelligent software in cars for improving the comfort of drivers, through entertainment applications, for instance, VoIP (Voice Over Internet Protocol) applications. In this type of networks due to the high mobility of vehicles there are a lot of losses when a handovers occurs. The handover process is a serious problem in vehicular networks,especially when we are running real-time applications such as VoIP. Therefore, it is important to develop mechanisms to enhance the management of handover in vehicular networks. The goal of this work is to propose a solution that underlying on a preregistration phase that is used to exchange security and QoS parameters previously to the occurrence of one handover. This solution was developed in order to achieve a secure handover with quality of service. The results obtained show that the solution can substantially reduce the number of handovers, improving this way the quality of the service in a VoIP application.