Relevant bibliographies by topics / Face authentication

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Face authentication'

Author: Grafiati
Published: 4 June 2021
Last updated: 20 February 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Face authentication.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Face authentication"

1

R.S., Dr Sabeenian. "Attendance Authentication System Using Face Recognition." Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (March 31, 2020): 1235–48. http://dx.doi.org/10.5373/jardcs/v12sp4/20201599.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Beumier, C., and M. Acheroy. "Automatic 3D face authentication." Image and Vision Computing 18, no. 4 (March 2000): 315–21. http://dx.doi.org/10.1016/s0262-8856(99)00052-9.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Chen, Xiang, Shouzhi Xu, Kai Ma, and Peng Chen. "Cross-Domain Identity Authentication Protocol of Consortium Blockchain Based on Face Recognition." Information 13, no. 11 (November 10, 2022): 535. http://dx.doi.org/10.3390/info13110535.

Full text
Abstract:
A consortium system can leverage information to improve workflows, accountability, and transparency through setting up a backbone for these cross-company and cross-discipline solutions, which make it become a hot spot of market application. Users of a consortium system may register and log in different target domains to get the access authentications, so how to access resources in different domains efficiently to avoid the trust-island problem is a big challenge. Cross-domain authentication is a kind of technology that breaks trust islands and enables users to access resources and services in different domains with the same credentials, which reduces service costs for all parties. Aiming at the problems of traditional cross-domain authentication, such as complex certificate management, low authentication efficiency, and being unable to prevent the attack users’ accounts, a cross-domain authentication protocol based on face recognition is proposed in this paper. The protocol makes use of the decentralized and distributed characteristics of the consortium chain to ensure the reliable transmission of data between participants without trust relationships, and achieves biometric authentication to further solve the problem of account attack by applying a deep-learning face-recognition model. An asymmetric encryption algorithm is used to encrypt and store the face feature codes on the chain to ensure the privacy of the user’s face features. Finally, through security analysis, it is proved that the proposed protocol can effectively prevent a man-in-the-middle attack, a replay attack, an account attack, an internal attack, and other attacks, and mutual security authentication between different domains can be realized with the protocol.
APA, Harvard, Vancouver, ISO, and other styles
4

Reddy, Reddy Phanidhar. "Voice and Face Recognition for Web Browser Security." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (November 30, 2021): 199–205. http://dx.doi.org/10.22214/ijraset.2021.38777.

Full text
Abstract:
Abstract: This paper analysis about browser privacy multimodal authentication mechanisms. Face and voice recognition will be used as authentication methods in this process. The OpenCV library is used in the framework's face recognition section. It detects and recognizes faces from a database using basic eigen face recognition approaches. The MFCC (Mel Frequency Cepstrum Coefficients) and Gaussian Mixture Model are used to recognize voices. Following successful authentication, the cookies on the local hard disc are decrypted, allowing us access to the browser cookies. Initially, after a user registers, we will encrypt the browser cookies with AES, one of the most secure encryption methods available. keywords: MFCC, Gaussian Mixture Model, Browser cookies, authentication, AES, encryption, decryption, Open CV, Eigen.
APA, Harvard, Vancouver, ISO, and other styles
5

Et. al., R. P. Dahake,. "Face Recognition from Video using Threshold based Clustering." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 1S (April 11, 2021): 272–85. http://dx.doi.org/10.17762/turcomat.v12i1s.1768.

Full text
Abstract:
Video processing has gained significant attention due to the rapid growth in video feed collected from a variety of domains. Face recognition and summary generation is gaining attention in the branch of video data processing. The recognition includes face identification from video frames and face authentication. The face authentication is nothing but labelling the faces. Face recognition strategies used in image processing techniques cannot be directly applied to video processing due to bulk data. The video processing techniques face multiple problems such as pose variation, expression variation, illumination variation, camera angles, etc. A lot of research work is done for face authentication in terms of accuracy and efficiency improvement. The second important aspect is the video summarization. Very few works have been done on the video summarization due to its complexity, computational overhead, and lack of appropriate training data. In some of the existing work analysing celebrity video for finding association in name node or face node of video dataset using graphical representation need script or dynamic caption details As well as there can be multiple faces of same person per frame so using K- Means clustering further for recognition purpose needs cluster count initially considering total person in the video. The proposed system works on video face recognition and summary generation. The system automatically identifies the front and profile faces of users. The similar faces are grouped together using threshold based a fixed-width clustering which is one of the novel approach in face recognition process best of our knowledge and only top k faces are used for authentication. This improves system efficiency. After face authentication, the occurrence count of each user is extracted and a visual co-occurrence graph is generated as a video summarization. The system is tested on the video dataset of multi persons occurring in different videos. Total 20 videos are consider for training and testing containing multiple person in one frame. To evaluate the accuracy of recognition. 80% of faces are correctly identified and authenticated from the video.
APA, Harvard, Vancouver, ISO, and other styles
6

Sadashiv, Wagh Kishor, Anushka Bagal, Abhijit Khatri, Maitrayee Dhumal, and Sofiya Shaikh. "Face and Voice Authentication System." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 1670–73. http://dx.doi.org/10.22214/ijraset.2022.42452.

Full text
Abstract:
Abstract: The issue of design and security is very predominant in any financial and business organization, especially such organization as a bank. Therefore, we intend to aid in security of the bank by bringing in an Artificial intelligence system that involves an individual to get an access to some items using face and voice recognition security system. This AI system is not just a normal password lock system that require a user to insert password and gain access to some items, it is a system that has an administrative authentication. In addition, with this kind of security authentication system we intend to implement, a highly secured AI feature, which enables the user with assured and highly secured transactions using their personal frame. Here an individual have to provide the face and voice authentication, which uses different algorithms, and is read by the AI server for clarification and verification. From this project, we hope to build an alternative and highly verified security for banks. Keywords: Artificial intelligence, administrative authentication, secured transactions, financial, business, organization.
APA, Harvard, Vancouver, ISO, and other styles
7

Hanafi, M., and W. A. W. Adnan. "Boosted Features for Face Authentication." Applied Mechanics and Materials 666 (October 2014): 276–81. http://dx.doi.org/10.4028/www.scientific.net/amm.666.276.

Full text
Abstract:
Boosted features developed using face signatures in combination with Gentle Adaboost algorithm offer alternative features for face authentication and face recognition. Face signatures are face representations extracted from Trace transform and Gentle Adaboost is used to enhance the performance of the features extracted from the face signatures. In this paper, we demonstrate the usefulness of the constructed features with experiments on BANCA database.
APA, Harvard, Vancouver, ISO, and other styles
8

Premkumar, J., K. Sughasri, Angel Preethi, and E. Kavitha. "Automized Pharmacy Using Face Authentication." Journal of Physics: Conference Series 1937, no. 1 (June 1, 2021): 012024. http://dx.doi.org/10.1088/1742-6596/1937/1/012024.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Guodong Guo, Lingyun Wen, and Shuicheng Yan. "Face Authentication With Makeup Changes." IEEE Transactions on Circuits and Systems for Video Technology 24, no. 5 (May 2014): 814–25. http://dx.doi.org/10.1109/tcsvt.2013.2280076.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Tistarelli, M., and E. Grosso. "Active vision-based face authentication." Image and Vision Computing 18, no. 4 (March 2000): 299–314. http://dx.doi.org/10.1016/s0262-8856(99)00059-1.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Face authentication"

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.

Full text
Abstract:
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.
APA, Harvard, Vancouver, ISO, and other styles
2

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.

Full text
Abstract:
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.
APA, Harvard, Vancouver, ISO, and other styles
3

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.

Full text
Abstract:
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.
APA, Harvard, Vancouver, ISO, and other styles
4

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.

Full text
Abstract:
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.
APA, Harvard, Vancouver, ISO, and other styles
5

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.

Full text
Abstract:
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.
APA, Harvard, Vancouver, ISO, and other styles
6

Akalin, Volkan. "Face Recognition Using Eigenfaces And Neural Networks." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1055912/index.pdf.

Full text
Abstract:
A face authentication system based on principal component analysis and neural networks is developed in this thesis. The system consists of three stages
preprocessing, 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.
APA, Harvard, Vancouver, ISO, and other styles
7

Tan, Teewoon. "HUMAN FACE RECOGNITION BASED ON FRACTAL IMAGE CODING." University of Sydney. Electrical and Information Engineering, 2004. http://hdl.handle.net/2123/586.

Full text
Abstract:
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.
APA, Harvard, Vancouver, ISO, and other styles
8

Tan, Teewoon. "HUMAN FACE RECOGNITION BASED ON FRACTAL IMAGE CODING." Thesis, The University of Sydney, 2003. http://hdl.handle.net/2123/586.

Full text
Abstract:
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.
APA, Harvard, Vancouver, ISO, and other styles
9

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.

Full text
Abstract:
Orientador: José Mario De Martino
Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
Made available in DSpace on 2018-08-23T20:06:41Z (GMT). No. of bitstreams: 1 Pereira_TiagodeFreitas_M.pdf: 17638731 bytes, checksum: 15a8d07214e3b31accd3218e5bde20cb (MD5) Previous issue date: 2013
Resumo: O Resumo poderá ser visualizado no texto completo da tese digital
Abstract: The complete Abstract is available with the full electronic document.
Mestrado
Engenharia de Computação
Mestre em Engenharia Elétrica
APA, Harvard, Vancouver, ISO, and other styles
10

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.

Full text
Abstract:
Made available in DSpace on 2015-05-14T12:36:38Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 2501696 bytes, checksum: a1f65e686060aa68aa5e43dee1e6c0b5 (MD5) Previous issue date: 2012-07-30
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
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.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Face authentication"

1

Real or fake: Studies in authentication. Lexington, Ky: University Press of Kentucky, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Baseball autograph handbook: A comprehensive guide to authentication and valuation of Hall of Fame autographs. Iola, Wis: Krause Publications, 1989.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Office, General Accounting. Electronic government: Planned e-Authentication gateway faces formidable development challenges : report to the Committee on Government Reform and the Subcommittee on Technology, Information Policy, Intergovernmental Relations, and the Census, House of Representatives. Washington, D.C: U.S. General Accounting Office, 2003.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Feng, Guocan, Tieniu Tan, Stan Z. Li, Yunhong Wang, and Jianhuang Lai. Advances in Biometric Person Authentication: 5th Chinese Conference on Biometric Recognition, SINOBIOMETRICS 2004, Guangzhou, China, December 13-14, 2004, Proceedings. Springer London, Limited, 2004.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Pankanti, Sharath, Tieniu Tan, Stan Z. Li, Gérard Chollet, and Zhenan Sun. Advances in Biometric Person Authentication: International Workshop on Biometric Recognition Systems, IWBRS 2005, Beijing, China, October 22 - 23, 2005, Proceedings. Springer London, Limited, 2005.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

(Editor), Stan Z. Li, Zhenan Sun (Editor), Tieniu Tan (Editor), Sharath Pankanti (Editor), Gérard Chollet (Editor), and David Zhang (Editor), eds. Advances in Biometric Person Authentication: International Workshop on Biometric Recognition Systems, IWBRS 2005, Beijing, China, October 22 23, 2005, Proceedings (Lecture Notes in Computer Science). Springer, 2005.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Nickell, Joe. Real or Fake: Studies in Authentication. University Press of Kentucky, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Nickell, Joe. Real or Fake: Studies in Authentication. University Press of Kentucky, 2009.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Baker, Mark Allen. Baseball autograph handbook: A comprehensive guide to authentication and valuation of Hall of Fame autographs. Krause Publications, 1990.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Face authentication"

1

Gutta, Srinivas, and Harry Wechsler. "Face Recognition Using Asymmetric Faces." In Biometric Authentication, 162–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_23.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Kompanets, Leonid. "Biometrics of Asymmetrical Face." In Biometric Authentication, 67–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_10.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Ngo, David C. L., Andrew B. J. Teoh, and Alwyn Goh. "Eigenspace-Based Face Hashing." In Biometric Authentication, 195–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_27.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Czyz, Jacek, Mohammad Sadeghi, Josef Kittler, and Luc Vandendorpe. "Decision Fusion for Face Authentication." In Biometric Authentication, 686–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_93.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Nanni, Loris, Annalisa Franco, and Raffalele Cappelli. "Towards a Robust Face Detector." In Biometric Authentication, 57–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25976-3_6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Cappelli, Raffaele, Dario Maio, and Davide Maltoni. "Subspace Classification for Face Recognition." In Biometric Authentication, 133–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47917-1_14.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Bigün, J., B. Duc, F. Smeraldi, S. Fischer, and A. Makarov. "Multi-Modal Person Authentication." In Face Recognition, 26–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-72201-1_2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Lu, Xiaoguang, Dirk Colbry, and Anil K. Jain. "Matching 2.5D Scans for Face Recognition." In Biometric Authentication, 30–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Tistarelli, Massimo, Andrea Lagorio, and Enrico Grosso. "Understanding Iconic Image-Based Face Biometrics." In Biometric Authentication, 19–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47917-1_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Wang, Xiaogang, and Xiaoou Tang. "Hallucinating Face by Eigentransformation with Distortion Reduction." In Biometric Authentication, 88–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_13.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Face authentication"

1

Barra, Silvio, Maria De Marsico, Chiara Galdi, Daniel Riccio, and Harry Wechsler. "FAME: Face Authentication for Mobile Encounter." In 2013 IEEE Workshop on Biometric Measurements and Systems for Security and Medical Applications (BIOMS). IEEE, 2013. http://dx.doi.org/10.1109/bioms.2013.6656140.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Hemery, B., J. Mahier, M. Pasquet, and C. Rosenberger. "Face Authentication for Banking." In First International Conference on Advances in Computer-Human Interaction. IEEE, 2008. http://dx.doi.org/10.1109/achi.2008.17.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Tanwar, Shivam, Pronika Chawla, Rosy Maadan, and Preet Bhadana. "Authentication of Face using Matlab." In 2020 5th International Conference on Communication and Electronics Systems (ICCES). IEEE, 2020. http://dx.doi.org/10.1109/icces48766.2020.9137979.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Zhang, Xinman, Kunlei Jing, Yixuan Dai, and Xuebin Xu. "Face Biometric Identity Authentication System." In 2018 IEEE 4th International Conference on Computer and Communications (ICCC). IEEE, 2018. http://dx.doi.org/10.1109/compcomm.2018.8780645.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Dabbah, M. A., W. L. Woo, and S. S. Dlay. "Secure Authentication for Face Recognition." In 2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/ciisp.2007.369304.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Zhou, Xinyan, Xiaoyu Ji, Chen Yan, Jiangyi Deng, and Wenyuan Xu. "NAuth: Secure Face-to-Face Device Authentication via Nonlinearity." In IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. IEEE, 2019. http://dx.doi.org/10.1109/infocom.2019.8737572.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Furuie, Ryo, Yuji Goda, and Lifeng Zhang. "Detecting Fake Face Input for Face Authentication by DCT with Compensating the Main Spindle Position of Face." In The 3rd IIAE International Conference on Intelligent Systems and Image Processing 2015. The Institute of Industrial Application Engineers, 2015. http://dx.doi.org/10.12792/icisip2015.032.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Zhang, Lifeng, Zhimei Yang, Takaharu Koda, and Hiroshi Kondo. "Face authentication using Orthogonal Transform signs." In 2006 International Symposium on Communications and Information Technologies. IEEE, 2006. http://dx.doi.org/10.1109/iscit.2006.339915.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Rosenberger, Christophe, and Luc Brun. "Similarity-based matching for face authentication." In 2008 19th International Conference on Pattern Recognition (ICPR). IEEE, 2008. http://dx.doi.org/10.1109/icpr.2008.4761860.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Mallauran, Caroline, Jean-Luc Dugelay, Florent Perronnin, and Christophe Garcia. "Online face detection and user authentication." In the 13th annual ACM international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1101149.1101185.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Face authentication"

1

Varastehpour, Soheil, Hamid Sharifzadeh, Iman Ardekani, and Abdolhossein Sarrafzadeh. Human Biometric Traits: A Systematic Review Focusing on Vascular Patterns. Unitec ePress, December 2020. http://dx.doi.org/10.34074/ocds.086.

Full text
Abstract:
Authentication methods based on human traits, including fingerprint, face, iris, and palm print, have developed significantly, and currently they are mature enough to be reliably considered for human identification purposes. Recently, as a new research area, a few methods based on non-facial skin features such as vein patterns have been developed. This literature review paper explores some key biometric systems such as face recognition, iris recognition, fingerprint, and palm print, and discusses their respective advantages and disadvantages; then by providing a comprehensive analysis of these traits, and their applications, vein pattern recognition is reviewed.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Face authentication' for particular source types:
Journal articles Dissertations / Theses
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography