Bibliografie tematiche / Fingerprint Verification

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Letteratura scientifica selezionata sul tema "Fingerprint Verification"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 19 febbraio 2022

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Articoli di riviste sul tema "Fingerprint Verification"

Bercelin, Rose Mary W., N. Subbulakshmi e Tofflin R. Bini. "Fingerprint Combination of Privacy Preservation is Improved by Delaunay Triangulation Method". Applied Mechanics and Materials 573 (giugno 2014): 437–41. http://dx.doi.org/10.4028/www.scientific.net/amm.573.437.

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Fingerprints are graphical ridge and valley patterns on the tips of human fingers. Owing to their uniqueness and permanence, the use of fingerprints is considered to be one of the most reliable methods of personal verification. Fingerprints are today among the most popularly used biometric modalities in automatic verification systems. At the same time, Protecting the privacy of Fingerprint is an important one, here a novel system propose protecting fingerprint by combining two different fingerprints. In the enrolment stage, fingerprints will be captured from two different fingers. Minutiae positions are extracted from one fingerprint (its the detailed pattern of the fingerprint). The orientation, (it indicates the flow of ridges and valleys) from other fingerprint, and the reference points are calculated from both the two fingerprints. Extracted combined minutiae templates are stored into database. Here A Delaunay Triangulation indexing scheme has been designed for protecting biometric template and non-invertible template are calculated for verifies the authorized person. By using the Delaunay triangulation method fingerprint privacy has to be improved.

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QIN, WEI, e YILONG YIN. "A NOVEL METHOD USING VIDEOS FOR FINGERPRINT VERIFICATION". International Journal of Pattern Recognition and Artificial Intelligence 26, n. 01 (febbraio 2012): 1256002. http://dx.doi.org/10.1142/s0218001412560022.

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Traditional fingerprint verifications use single image for matching. However, the verification accuracy cannot meet the need of some application domains. In this paper, we propose to use videos for fingerprint verification. To take full use of the information contained in fingerprint videos, we present a novel method to use the dynamic as well as the static information in fingerprint videos. After preprocessing and aligning processes, the Inclusion Ratio of two matching fingerprint videos is calculated and used to represent the similarity between these two videos. Experimental results show that video-based method can access better accuracy than the method based on single fingerprint.

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Upendra, K., S. Singh, V. Kumar e H. K. Verma. "Online fingerprint verification". Journal of Medical Engineering & Technology 31, n. 1 (gennaio 2007): 36–45. http://dx.doi.org/10.1080/03091900500324194.

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Djara, Tahirou, Marc Kokou Assogba e Antoine Vianou. "A Contactless Fingerprint Verification Method using a Minutiae Matching Technique". International Journal of Computer Vision and Image Processing 6, n. 1 (gennaio 2016): 12–27. http://dx.doi.org/10.4018/ijcvip.2016010102.

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Most of matching or verification phases of fingerprint systems use minutiae types and orientation angle to find matched minutiae pairs from the input and template fingerprints. Unfortunately, due to some non-linear distortions, like excessive pressure and fingers twisting during enrollment, this process can cause the minutiae features to be distorted from the original. The authors are then interested in a fingerprint matching method using contactless images for fingerprint verification. After features extraction, they compute Euclidean distances between template minutiae (bifurcation and ending points) and input image minutiae. They compute then after bifurcation ridges orientation angles and ending point orientations. In the decision stage, they analyze the similarity between templates. The proposed algorithm has been tested on a set of 420 fingerprint images. The verification accuracy is found to be acceptable and the experimental results are promising.

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Khan, Sajid, Dong-Ho Lee, Asif Khan, Ahmad Waqas, Abdul Rehman Gilal e Zahid Hussain Khand. "A Digital Camera-Based Rotation-Invariant Fingerprint Verification Method". Scientific Programming 2020 (15 maggio 2020): 1–10. http://dx.doi.org/10.1155/2020/9758049.

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Fingerprint registration and verification is an active area of research in the field of image processing. Usually, fingerprints are obtained from sensors; however, there is recent interest in using images of fingers obtained from digital cameras instead of scanners. An unaddressed issue in the processing of fingerprints extracted from digital images is the angle of the finger during image capture. To match a fingerprint with 100% accuracy, the angles of the matching features should be similar. This paper proposes a rotation and scale-invariant decision-making method for the intelligent registration and recognition of fingerprints. A digital image of a finger is taken as the input and compared with a reference image for derotation. Derotation is performed by applying binary segmentation on both images, followed by the application of speeded up robust feature (SURF) extraction and then feature matching. Potential inliers are extracted from matched features by applying the M-estimator. Matched inlier points are used to form a homography matrix, the difference in the rotation angles of the finger in both the input and reference images is calculated, and finally, derotation is performed. Input fingerprint features are extracted and compared or stored based on the decision support system required for the situation.

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Cappelli, Raffaele, Matteo Ferrara, Annalisa Franco e Davide Maltoni. "Fingerprint verification competition 2006". Biometric Technology Today 15, n. 7-8 (luglio 2007): 7–9. http://dx.doi.org/10.1016/s0969-4765(07)70140-6.

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Mesec, Chip. "Fingerprint identification versus verification". Biometric Technology Today 15, n. 9 (settembre 2007): 7. http://dx.doi.org/10.1016/s0969-4765(07)70157-1.

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Qin, Wei, Yilong Yin e Lili Liu. "Video-Based Fingerprint Verification". Sensors 13, n. 9 (4 settembre 2013): 11660–86. http://dx.doi.org/10.3390/s130911660.

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Maio, D., D. Maltoni, R. Cappelli, J. L. Wayman e A. K. Jain. "FVC2000: fingerprint verification competition". IEEE Transactions on Pattern Analysis and Machine Intelligence 24, n. 3 (marzo 2002): 402–12. http://dx.doi.org/10.1109/34.990140.

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Jain, A., Lin Hong e R. Bolle. "On-line fingerprint verification". IEEE Transactions on Pattern Analysis and Machine Intelligence 19, n. 4 (aprile 1997): 302–14. http://dx.doi.org/10.1109/34.587996.

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Tesi sul tema "Fingerprint Verification"

Yager, Neil Gordon Computer Science &amp Engineering Faculty of Engineering UNSW. "Hierarchical fingerprint verification". Awarded by:University of New South Wales. Computer Science and Engineering, 2006. http://handle.unsw.edu.au/1959.4/27008.

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Fingerprints have been an invaluable tool for law enforcement and forensics for over a century, motivating research into automated fingerprint based identification in the early 1960's. More recently, fingerprints have found an application in the emerging industry of biometric systems. Biometrics is the automatic identification of an individual based on physiological or behavioral characteristics. Due to its security related applications and the current world political climate, biometrics is presently the subject of intense research by private and academic institutions. Fingerprints are emerging as the most common and trusted biometric for personal identification. However, despite decades of intense research there are still significant challenges for the developers of automated fingerprint verification systems. This thesis includes an examination of all major stages of the fingerprint verification process, with contributions made at each step. The primary focus is upon fingerprint registration, which is the challenging problem of aligning two prints in order to compare their corresponding features for verification. A hierarchical approach is proposed consisting of three stages, each of which employs novel features and techniques for alignment. Experimental results show that the hierarchical approach is robust and outperforms competing state-of-the-art registration methods from the literature. However, despite its power, like most algorithms it has limitations. Therefore, a novel method of information fusion at the registration level has been developed. The technique dynamically selects registration parameters from a set of competing algorithms using a statistical framework. This allows for the relative advantages of different approaches to be exploited. The results show a significant improvement in alignment accuracy for a wide variety of fingerprint databases. Given a robust alignment of two fingerprints, it still remains to be verified whether or not they have originated from the same finger. This is a non-trivial problem, and a close examination of fingerprint features available for this task is conducted with extensive experimental results.

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Deng, Huimin. "Robust minutia-based fingerprint verification". Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37036427.

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Deng, Huimin, e 鄧惠民. "Robust minutia-based fingerprint verification". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37036427.

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Yan, Weiwei. "Software-hardware Cooperative Embedded Verification System Fusing Fingerprint Verification and Shared-key Authentication". Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-66677.

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In order to protect the security of the commercial information, personnel information, military information, governmental information on the Internet, the claimed identity should be authenticated. Now there are three main security authentication methods: first: using user PIN, such as password; second: using physical key, such as USBKey; third: using biological authentication technology, such as fingerprint, iris, voice and palm prints, etc. Because of the uniqueness, invariance, and ubiquity properties of biometric authentication, biometric authentication is becoming popular, especially fingerprint recognition. However, when the fingerprint recognition information is transported on the public channel, it may be attacked, such as the fingerprint information is stolen. So a cryptology mechanism is needed to protect the fingerprint recognition information. In the field of embedded security authentication system, the traditional hardware implementation mechanism, such as ASIC, can satisfy requires of functions and performances, but it is not configurable, flexible, and easy to expand; the traditional software implementation mechanism, such as general purpose processor, is flexible, but the cost and the power consumption are higher than hardware implementation. In order to take the advantages of biometrics, cryptology, hardware implementation, and software implementation, a hardware-software cooperating embedded authentication system based on shared-key authentication and fingerprint verification is proposed. First, this system authenticates the identities of client and server by shared-key authentication, creates the current encrypt key and hash key, and then authenticates the identity of them via fingerprint recognition. During fingerprint recognition, the information of fingerprint is not needed to transmit over the public channel, so the security of fingerprint is increased. Theoretic analysis and experiments show that, this system reach very high authentication rate and security. This system can resist replay attack, server template attack, device template attack, effectively.

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Sandström, Marie. "Liveness Detection in Fingerprint Recognition Systems". Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2397.

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Biometrics deals with identifying individuals with help of their biological data. Fingerprint scanning is the most common method of the biometric methods available today. The security of fingerprint scanners has however been questioned and previous studies have shown that fingerprint scanners can be fooled with artificial fingerprints, i.e. copies of real fingerprints. The fingerprint recognition systems are evolving and this study will discuss the situation of today.

Two approaches have been used to find out how good fingerprint recognition systems are in distinguishing between live fingers and artificial clones. The first approach is a literature study, while the second consists of experiments.

A literature study of liveness detection in fingerprint recognition systems has been performed. A description of different liveness detection methods is presented and discussed. Methods requiring extra hardware use temperature, pulse, blood pressure, electric resistance, etc., and methods using already existent information in the system use skin deformation, pores, perspiration, etc.

The experiments focus on making artificial fingerprints in gelatin from a latent fingerprint. Nine different systems were tested at the CeBIT trade fair in Germany and all were deceived. Three other different systems were put up against more extensive tests with three different subjects. All systems werecircumvented with all subjects'artificial fingerprints, but with varying results. The results are analyzed and discussed, partly with help of the A/R value defined in this report.

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Fransson, Linda, e Therese Jeansson. "Biometric methods and mobile access control". Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5023.

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Our purpose with this thesis was to find biometric methods that can be used in access control of mobile access. The access control has two parts. Firstly, to validate the identity of the caller and, secondly, to ensure the validated user is not changed during the session that follows. Any solution to the access control problem is not available today, which means that anyone can get access to the mobile phone and the Internet. Therefore we have researched after a solution that can solve this problem but also on how to secure that no one else can take over an already validated session. We began to search for biometric methods that are available today to find them that would be best suited together with a mobile phone. After we had read information about them we did choose three methods for further investigation. These methods were Fingerprint Recognition, Iris Scan and Speaker Verification. Iris Scan is the method that is best suited to solve the authentication problem. The reasons for this are many. One of them is the uniqueness and stability of the iris, not even identical twins or the pair of the same individual has the same iris minutiae. The iris is also very protected behind eyelids, cornea and the aqueous humor and therefore difficult to damage. When it comes to the method itself, is it one of the most secure methods available today. One of the reasons for this is that the equal error rate is better than one in a million. However, this rate can be even better. It all depends on the Hamming Distance, which is a value that show how different the saved and temporarily template are, and what it is set to. To solve our session authentication, which was to make sure that no one else could take over a connected mobile phone, a sensor plate is the answer. This sensor will be able to sense for touch, heat and pulse. These three sensor measurements will together secure a validated session since the mobile phone will disconnect if the sensor looses its sensor data. There are, however, technological and other challenges to be solved before our proposed solutions will become viable. We address some of these issues in our thesis.

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Sun, Wei [Verfasser], Thomas [Akademischer Betreuer] Sikora, Thomas [Gutachter] Sikora, Atta [Gutachter] Badii e Ivo [Gutachter] Keller. "Low complexity embedded fingerprint verification and identification system / Wei Sun ; Gutachter: Thomas Sikora, Atta Badii, Ivo Keller ; Betreuer: Thomas Sikora". Berlin : Technische Universität Berlin, 2016. http://d-nb.info/1156181704/34.

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Dimitrov, Emanuil. "Fingerprints recognition". Thesis, Växjö University, School of Mathematics and Systems Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-5522.

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Nowadays biometric identification is used in a variety of applications-administration, business and even home. Although there are a lot of biometric identifiers, fingerprints are the most widely spread due to their acceptance from the people and the cheap price of the hardware equipment. Fingerprint recognition is a complex image recognition problem and includes algorithms and procedures for image enhancement and binarization, extracting and matching features and sometimes classification. In this work the main approaches in the research area are discussed, demonstrated and tested in a sample application. The demonstration software application is developed by using Verifinger SDK and Microsoft Visual Studio platform. The fingerprint sensor for testing the application is AuthenTec AES2501.

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Falade, Joannes Chiderlos. "Identification rapide d'empreintes digitales, robuste à la dissimulation d'identité". Thesis, Normandie, 2020. http://www.theses.fr/2020NORMC231.

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La biométrie est de plus en plus utilisée à des fins d’identification compte tenu de la relation étroite entre la personne et son identifiant (comme une empreinte digitale). Nous positionnons cette thèse sur la problématique de l’identification d’individus à partir de ses empreintes digitales. L’empreinte digitale est une donnée biométrique largement utilisée pour son efficacité, sa simplicité et son coût d’acquisition modeste. Les algorithmes de comparaison d’empreintes digitales sont matures et permettent d’obtenir en moins de 500 ms un score de similarité entre un gabarit de référence (stocké sur un passeport électronique ou une base de données) et un gabarit acquis. Cependant, il devient très important de déterminer l'identité d'un individu contre une population entière en un temps très court (quelques secondes). Ceci représente un enjeu important compte tenu de la taille de la base de données biométriques (contenant un ensemble d’individus de l’ordre d’un pays). Par exemple, avant de délivrer un nouveau passeport à un individu qui en fait la demande, il faut faire une recherche d'identification sur la base des données biométriques du pays afin de s'assurer que ce dernier n'en possède pas déjà un autre mais avec les mêmes empreintes digitales (éviter les doublons). Ainsi, la première partie du sujet de cette thèse concerne l’identification des individus en utilisant les empreintes digitales. D’une façon générale, les systèmes biométriques ont pour rôle d’assurer les tâches de vérification (comparaison 1-1) et d’identification (1-N). Notre sujet se concentre sur l’identification avec N étant à l’échelle du million et représentant la population d’un pays par exemple. Dans le cadre de nos travaux, nous avons fait un état de l’art sur les méthodes d’indexation et de classification des bases de données d’empreintes digitales. Nous avons privilégié les représentations binaires des empreintes digitales pour indexation. Tout d’abord, nous avons réalisé une étude bibliographique et rédigé un support sur l’état de l’art des techniques d’indexation pour la classification des empreintes digitales. Ensuite, nous avons explorer les différentes représentations des empreintes digitales, puis réaliser une prise en main et l’évaluation des outils disponibles à l’imprimerie Nationale (IN Groupe) servant à l'extraction des descripteurs représentant une empreinte digitale. En partant de ces outils de l’IN, nous avons implémenté quatre méthodes d’identification sélectionnées dans l’état de l’art. Une étude comparative ainsi que des améliorations ont été proposées sur ces méthodes. Nous avons aussi proposé une nouvelle solution d'indexation d'empreinte digitale pour réaliser la tâche d’identification qui améliore les résultats existant. Les différents résultats sont validés sur des bases de données de tailles moyennes publiques et nous utilisons le logiciel Sfinge pour réaliser le passage à l’échelle et la validation complète des stratégies d’indexation. Un deuxième aspect de cette thèse concerne la sécurité. Une personne peut avoir en effet, la volonté de dissimuler son identité et donc de mettre tout en œuvre pour faire échouer l’identification. Dans cette optique, un individu peut fournir une empreinte de mauvaise qualité (portion de l’empreinte digitale, faible contraste en appuyant peu sur le capteur…) ou fournir une empreinte digitale altérée (empreinte volontairement abîmée, suppression de l’empreinte avec de l’acide, scarification…). Il s'agit donc dans la deuxième partie de cette thèse de détecter les doigts morts et les faux doigts (silicone, impression 3D, empreinte latente) utilisés par des personnes mal intentionnées pour attaquer le système. Nous avons proposé une nouvelle solution de détection d'attaque basée sur l'utilisation de descripteurs statistiques sur l'empreinte digitale. Aussi, nous avons aussi mis en place trois chaînes de détections des faux doigts utilisant les techniques d'apprentissages profonds
Biometrics are increasingly used for identification purposes due to the close relationship between the person and their identifier (such as fingerprint). We focus this thesis on the issue of identifying individuals from their fingerprints. The fingerprint is a biometric data widely used for its efficiency, simplicity and low cost of acquisition. The fingerprint comparison algorithms are mature and it is possible to obtain in less than 500 ms a similarity score between a reference template (enrolled on an electronic passport or database) and an acquired template. However, it becomes very important to check the identity of an individual against an entire population in a very short time (a few seconds). This is an important issue due to the size of the biometric database (containing a set of individuals of the order of a country). Thus, the first part of the subject of this thesis concerns the identification of individuals using fingerprints. Our topic focuses on the identification with N being at the scale of a million and representing the population of a country for example. Then, we use classification and indexing methods to structure the biometric database and speed up the identification process. We have implemented four identification methods selected from the state of the art. A comparative study and improvements were proposed on these methods. We also proposed a new fingerprint indexing solution to perform the identification task which improves existing results. A second aspect of this thesis concerns security. A person may want to conceal their identity and therefore do everything possible to defeat the identification. With this in mind, an individual may provide a poor quality fingerprint (fingerprint portion, low contrast by lightly pressing the sensor...) or provide an altered fingerprint (impression intentionally damaged, removal of the impression with acid, scarification...). It is therefore in the second part of this thesis to detect dead fingers and spoof fingers (silicone, 3D fingerprint, latent fingerprint) used by malicious people to attack the system. In general, these methods use machine learning techniques and deep learning. Secondly, we proposed a new presentation attack detection solution based on the use of statistical descriptors on the fingerprint. Thirdly, we have also build three presentation attacks detection workflow for fake fingerprint using deep learning. Among these three deep solutions implemented, two come from the state of the art; then the third an improvement that we propose. Our solutions are tested on the LivDet competition databases for presentation attack detection

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Bartoň, Jaroslav. "Podpora pro autentizaci pomocí otisků prstu". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-235492.

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The goal of the thesis is the finger-print authentication support within the Linux operating system and the K Desktop Environment (KDE). Theoretical part of the thesis firstly explains main IT security terms and ways to proof the identity. Secondly it describes biometric systems and types of processed biometric characteristics. Lastly the features of finger-prints, their markants as well as types of scanners used in scanning the finger-prints and ways to analyze the scanned material have been elaborated. Practical solution part of the thesis develops and establishes finger-print management application and plugin for KDM graphics login manager.

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Più fonti

Libri sul tema "Fingerprint Verification"

1942-, Wilson C. L., e National Institute of Standards and Technology (U.S.), a cura di. Studies of fingerprint matching using the NIST verification test bed (VTB). [Gaithersburg, Md.]: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 2003.

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Capitoli di libri sul tema "Fingerprint Verification"

Venkataramani, Krithika, e B. V. K. Vijaya Kumar. "Fingerprint Verification Using Correlation Filters". In Lecture Notes in Computer Science, 886–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44887-x_103.

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Maio, Dario, Davide Maltoni, Raffaele Cappelli, Jim L. Wayman e Anil K. Jain. "FVC2004: Third Fingerprint Verification Competition". In Biometric Authentication, 1–7. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_1.

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Jain, Anil K., Sharath Pankanti, Salil Prabhakar e Arun Ross. "Recent Advances in Fingerprint Verification". In Lecture Notes in Computer Science, 182–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45344-x_26.

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Udup U., Raghavendra, Gaurav Garg e Pramod Sharma. "Fast and Accurate Fingerprint Verification". In Lecture Notes in Computer Science, 192–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45344-x_27.

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Prabhakar, Salil, e Anil K. Jain. "Decision-Level Fusion in Fingerprint Verification". In Multiple Classifier Systems, 88–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-48219-9_9.

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Ceguerra, Anna, e Irena Koprinska. "Automatic Fingerprint Verification Using Neural Networks". In Artificial Neural Networks — ICANN 2002, 1281–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-46084-5_207.

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Kerschbaum, Florian, Mikhail J. Atallah, David M’Raïhi e John R. Rice. "Private Fingerprint Verification without Local Storage". In Biometric Authentication, 387–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_54.

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Gil, Younhee, Daesung Moon, Sungbum Pan e Yongwha Chung. "Fingerprint Verification System Involving Smart Card". In Lecture Notes in Computer Science, 510–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36552-4_35.

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Gao, Q., e G. S. Moschytz. "A CNN-based Fingerprint Verification System". In Springer Proceedings in Physics, 243–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-30636-6_27.

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Altman, Micah. "A Fingerprint Method for Scientific Data Verification". In Advances in Computer and Information Sciences and Engineering, 311–16. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-8741-7_57.

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Atti di convegni sul tema "Fingerprint Verification"

Wenzl, Matthias, e Daniel Kluka. "Adding Channel Security to a Fingerprint Verification Chain". In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-67356.

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Authenticating persons using fingerprints is a widely accepted method in the field of access control, border control, prosecution and many others. Today, fingerprint modules with customizable firmware can be bought commercially off the shelf by hobbyists and small companies to be used in their applications and are usually locally separated from a controller implementing the feature extraction and comparison algorithms. As a matter of fact, the communication channel between the sensor and the controller module is susceptible to eavesdropping and man in the middle attacks. Nevertheless, adding communication channel security to such a system has a direct negative impact on the system’s response time, thus directly affecting user acceptance. The aim of this paper is to provide a comprehensive investigation on measures to counter run-time degredation when adding communication channel security on behalf of an existing fingerprint verification chain. We show that a combination of the elliptic curve Diffie-Hellman key exchange together with AES-256 and the use of parallelization using OpenMP on a controller node leads to an acceptable run time making key creation and exchange upon every fingerprint read request a suitable undertaking.

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Khalil, Mohammed S., Dzulkifli Muhammad, Muhammad Khurram Khan e Qais AL-Nuzaili. "Fingerprint verification using fingerprint texture". In 2009 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2009. http://dx.doi.org/10.1109/isspit.2009.5407549.

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Jain, A., e Lin Hong. "On-line fingerprint verification". In Proceedings of 13th International Conference on Pattern Recognition. IEEE, 1996. http://dx.doi.org/10.1109/icpr.1996.547016.

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Qin, Wei, Yilong Yin, Chunxiao Ren e Lili Liu. "Video-based fingerprint verification". In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5495472.

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Baradarani, A., J. R. B. Taylor, F. Severin e R. Gr Maev. "Advanced fingerprint verification software". In SPIE Defense + Security, a cura di Edward M. Carapezza. SPIE, 2016. http://dx.doi.org/10.1117/12.2224244.

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Khalil, Mohammed S., Dzulkifli Muhammad e Qais AL-Nuzaili. "Fingerprint Verification Using the Texture of Fingerprint Image". In 2009 Second International Conference on Machine Vision. IEEE, 2009. http://dx.doi.org/10.1109/icmv.2009.18.

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Marupudi, Naveena, Eugene John e Fred Hudson. "Fingerprint verification in multimodal biometrics". In 2006 IEEE Region 5 Conference. IEEE, 2006. http://dx.doi.org/10.1109/tpsd.2006.5507443.

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Cappelli, Raffaele, Matteo Ferrara, Davide Maltoni e Francesco Turroni. "Fingerprint verification competition at IJCB2011". In 2011 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2011. http://dx.doi.org/10.1109/ijcb.2011.6117488.

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Sanjekar, Priti S., e Priyadarshan S. Dhabe. "Fingerprint verification using haar wavelet". In 2010 2nd International Conference on Computer Engineering and Technology. IEEE, 2010. http://dx.doi.org/10.1109/iccet.2010.5485896.

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Leon, J., G. Sanchez, G. Aguilar, L. Toscano, H. Perez e J. M. Ramirez. "Fingerprint verification applying invariant moments". In 2009 52nd IEEE International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2009. http://dx.doi.org/10.1109/mwscas.2009.5235878.

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Rapporti di organizzazioni sul tema "Fingerprint Verification"

Wilson, Charles L., Craig I. Watson, Michael D. Garris e Austin Hicklin. Studies of fingerprint matching using the NIST verification test bed (VTB). Gaithersburg, MD: National Institute of Standards and Technology, 2003. http://dx.doi.org/10.6028/nist.ir.7020.

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