Relevant bibliographies by topics / Biometric performance

Contents

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

Academic literature on the topic 'Biometric performance'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Biometric performance"

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Bhirud, Priya, and Nandana Prabhu. "Performance Evaluation of Filters of Discrete Wavelet Transforms for Biometrics." International Journal of Informatics and Communication Technology (IJ-ICT) 3, no. 2 (August 1, 2014): 97. http://dx.doi.org/10.11591/ijict.v3i2.pp97-102.

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<p>Biometrics associated with automated methods of identifying a person or verifying the identity of a person based on physiological or behavioral characteristics. Commonly used biometric features are facial features, fingerprints, voice, facial thermo grams, iris, posture/gait, palm print, hand geometry etc. Compared with other biometric characteristics iris is the most stable and hence the most reliable biometric characteristic over the period of a lifetime. This proposed work provides comparative study of various filters of Wavelet Transforms in terms of size and PSNR of images<em>.</em></p>
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S. Raju, A., and V. Udayashankara. "A Survey on Unimodal, Multimodal Biometrics and Its Fusion Techniques." International Journal of Engineering & Technology 7, no. 4.36 (December 9, 2018): 689. http://dx.doi.org/10.14419/ijet.v7i4.36.24224.

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Presently, a variety of biometric modalities are applied to perform human identification or user verification. Unimodal biometric systems (UBS) is a technique which guarantees authentication information by processing distinctive characteristic sequences and these are fetched out from individuals. However, the performance of unimodal biometric systems restricted in terms of susceptibility to spoof attacks, non-universality, large intra-user variations, and noise in sensed data. The Multimodal biometric systems defeat various limitations of unimodal biometric systems as the sources of different biometrics typically compensate for the inherent limitations of one another. The objective of this article is to analyze various methods of information fusion for biometrics, and summarize, to conclude with direction on future research proficiency in a multimodal biometric system using ECG, Fingerprint and Face features. This paper is furnished as a ready reckoner for those researchers, who wish to persue their work in the area of biometrics.
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Sabharwal, Munish. "Multi-Modal Biometric Authentication and Secure Transaction Operation Framework for E-Banking." International Journal of Business Data Communications and Networking 13, no. 1 (January 2017): 102–16. http://dx.doi.org/10.4018/ijbdcn.2017010109.

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The rationale of the research work is to suggest a multi-modal biometric authentication and secure transaction operation framework for E-Banking. The literature survey identifies the various types of E-Banking Channels available as on-date, the various types of biometric technologies available as on-date as well the significant metrics affecting their performance while deploying them in various different e-banking channels. The performance analysis of various types of biometric technologies based on significant metrics for Biometrics Implementation further identifies the currently implementable biometric technologies for the various different e-banking channels. Subsequently a requirement analysis of potential e-banking channels is followed by System Suitability Analysis to identify which multi-biometrics and support mechanisms are suitable for particular e-banking channels. The final conclusion suggests a viable multi-modal biometric authentication and secure transaction operation framework for various e-banking channels.
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Rasiah, Devinaga, and Yuen Yee Yen. "User acceptance of ATM biometric authentication." Global Journal of Computer Sciences: Theory and Research 10, no. 1 (April 30, 2020): 11–17. http://dx.doi.org/10.18844/gjcs.v10i1.4748.

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Malaysia is amongst one of the first countries in the world to use biometrics as a standard in its identification cards and automatic teller machines (ATMs). Currently, there is a lack of studies in Malaysia and around the world that studied the user acceptance of ATM biometric authentication technology. All previous studies tended to overlook the user acceptance of ATM biometrics authentication which is an increasingly important mechanism to verify user identity in banking industry. Therefore, this study is carried out to examine the key factors of user acceptance of ATM biometric authentication technology in Malaysian banks. The target population of this study was customers of commercial banks in the central region of Malaysia. The participants were randomly selected. The questionnaire was distributed to 200 bank customers who have at least 1-year experience in using ATM biometric authentication. The items in the questionnaire were derived from the extensive survey of relevant literature and oral interview. The findings show that both the performance expectancy and social influence have significant effects on user adoption of ATM biometric authentication. Keywords: ATM, behavioural intention to use, biometrics, performance expectancy, social influence.
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Punithavathi, P., and S. Geetha. "Random Projection-based Cancelable Template Generation for Sparsely Distributed Biometric Patterns." Indonesian Journal of Electrical Engineering and Computer Science 7, no. 3 (September 1, 2017): 877. http://dx.doi.org/10.11591/ijeecs.v7.i3.pp877-886.

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Cancelable biometrics, a template transformation approach, attempts to provide robustness for authentication services based on biometrics. Several biometric template protection techniques represent the biometric information in binary form as it provides benefits in matching and storage. In this context, it becomes clear that often such transformed binary representations can be easily compromised and breached. In this paper, we propose an efficient non-invertible template transformation approach using random projection technique and Discrete Fourier transformation to shield the binary biometric representations. The cancelable fingerprint templates designed by the proposed technique meets the requirements of revocability, diversity, non-invertibility and performance. The matching performance of the cancelable fingerprint templates generated using proposed technique, have improved when compared with the state-of-art methods.
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Moujahdi, Chouaib, George Bebis, Sanaa Ghouzali, Mounia Mikram, and Mohammed Rziza. "Biometric Template Protection Using Spiral Cube: Performance and Security Analysis." International Journal on Artificial Intelligence Tools 25, no. 01 (February 2016): 1550027. http://dx.doi.org/10.1142/s021821301550027x.

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Personal authentication systems based on biometrics have given rise to new problems and challenges related to the protection of personal data, issues of less concern in traditional authentication systems. The irrevocability of biometric templates makes biometric systems very vulnerable to several attacks. In this paper we present a new approach for biometric template protection. Our objective is to build a non-invertible transformation, based on random projection, which meets the requirements of revocability, diversity, security and performance. In this context, we use the chaotic behavior of logistic map to build the projection vectors using a methodology that makes the construction of the projection matrix depend on the biometric template and its identity. The proposed approach has been evaluated and compared with Biohashing and BioPhasor using a rigorous security analysis. Our extensive experimental results using several databases (e.g., face, finger-knuckle and iris), show that the proposed technique has the ability to preserve and increase the performance of protected systems. Moreover, it is demonstrated that the security of the proposed approach is sufficiently robust to possible attacks keeping an acceptable balance between discrimination, diversity and non-invertibility.
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NAZAR, AKIF, ISSA TRAORÉ, and AHMED AWAD E. AHMED. "INVERSE BIOMETRICS FOR MOUSE DYNAMICS." International Journal of Pattern Recognition and Artificial Intelligence 22, no. 03 (May 2008): 461–95. http://dx.doi.org/10.1142/s0218001408006363.

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Various techniques have been proposed in different literature to analyze biometric samples collected from individuals. However, not a lot of attention has been paid to the inverse problem, which consists of synthesizing artificial biometric samples that can be used for testing existing biometric systems or protecting them against forgeries. In this paper, we present a framework for mouse dynamics biometrics synthesis. Mouse dynamics biometric is a behavioral biometric technology, which allows user recognition based on the actions received from the mouse input device while interacting with a graphical user interface. The proposed inverse biometric model learns from random raw samples collected from real users and then creates synthetic mouse actions for fake users. The generated mouse actions have unique behavioral properties separate from the real mouse actions. This is shown through various comparisons of behavioral metrics as well as a Kolmogorov–Smirnov test. We also show through a two-fold cross-validation test that by submitting sample synthetic data to an existing mouse biometrics analysis model we achieve comparable performance results as when the model is applied to real mouse data.
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Barzut, Srđan, Milan Milosavljević, Saša Adamović, Muzafer Saračević, Nemanja Maček, and Milan Gnjatović. "A Novel Fingerprint Biometric Cryptosystem Based on Convolutional Neural Networks." Mathematics 9, no. 7 (March 28, 2021): 730. http://dx.doi.org/10.3390/math9070730.

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Modern access controls employ biometrics as a means of authentication to a great extent. For example, biometrics is used as an authentication mechanism implemented on commercial devices such as smartphones and laptops. This paper presents a fingerprint biometric cryptosystem based on the fuzzy commitment scheme and convolutional neural networks. One of its main contributions is a novel approach to automatic discretization of fingerprint texture descriptors, entirely based on a convolutional neural network, and designed to generate fixed-length templates. By converting templates into the binary domain, we developed the biometric cryptosystem that can be used in key-release systems or as a template protection mechanism in fingerprint matching biometric systems. The problem of biometric data variability is marginalized by applying the secure block-level Bose–Chaudhuri–Hocquenghem error correction codes, resistant to statistical-based attacks. The evaluation shows significant performance gains when compared to other texture-based fingerprint matching and biometric cryptosystems.
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Paul, Padma P., and Marina L. Gavrilova. "A Novel Cross Folding Algorithm for Multimodal Cancelable Biometrics." International Journal of Software Science and Computational Intelligence 4, no. 3 (July 2012): 20–37. http://dx.doi.org/10.4018/jssci.2012070102.

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Multimodal biometric systems have emerged as highly successful new approach to combat problems of unimodal biometric system such as intraclass variability, interclass similarity, data quality, non-universality, and sensitivity to noise. However, one major issue pertinent to unimodal system remains, which has to do with actual biometric characteristics of users being permanent and their number being limited. Thus, if a user’s biometric is compromised, it might be impossible or highly difficult to replace it in a particular system. The concept of cancelable biometric or cancelability is to transform a biometric data or feature into a new one so that the stored biometric template can be easily changed in a biometric security system. In this paper, the authors present a novel solution for cancelable biometrics in a multimodal system. They develop a new cancelable biometric template generation algorithm using random projection and transformation-based feature extraction and selection. Performance of the proposed algorithm is validated on a virtual multi-modal face and ear database.
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Omar, Bayan. "Fusion Method with Mean-discrete Algorithm in Feature level for Identical twins Identification." UHD Journal of Science and Technology 4, no. 2 (December 27, 2020): 141. http://dx.doi.org/10.21928/uhdjst.v4n2y2020.pp141-150.

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The study on twins is an important form of study in the forensic and biometrics field as twins share similar genetic traits. A biometric is one of the common types of pattern recognition which acquires biometric data from a person. From these data, a feature is established and extracted where these features can be used to identify individual. Exiting works in biometric identification concentrate on unimodal biometric identification. The high similarity in a pair of twin’s biometric may lead to miss performance. Hence, due to their great accurateness, multimodal biometric systems have become more favored than unimodal biometric systems in identical twins identification. However, these systems are highly complex. We proposed Mean-Discrete feature based fusion algorithm for Kurdish handwriting and fingerprint for identical twins detection. Its viability and advantage over the unimodal biometric systems are highlighted. This paper employed 800 images from 50 pairs of identical twins from Kurdistan Region to carry out the experiment.
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Dissertations / Theses on the topic "Biometric performance"

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Almayyan, Waheeda. "Performance analysis of multimodal biometric fusion." Thesis, De Montfort University, 2012. http://hdl.handle.net/2086/5998.

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Biometrics is constantly evolving technology which has been widely used in many official and commercial identification applications. In fact in recent years biometric-based authentication techniques received more attention due to increased concerns in security. Most biometric systems that are currently in use typically employ a single biometric trait. Such systems are called unibiometric systems. Despite considerable advances in recent years, there are still challenges in authentication based on a single biometric trait, such as noisy data, restricted degree of freedom, intra-class variability, non-universality, spoof attack and unacceptable error rates. Some of the challenges can be handled by designing a multimodal biometric system. Multimodal biometric systems are those which utilize or are capable of utilizing, more than one physiological or behavioural characteristic for enrolment, verification, or identification. In this thesis, we propose a novel fusion approach at a hybrid level between iris and online signature traits. Online signature and iris authentication techniques have been employed in a range of biometric applications. Besides improving the accuracy, the fusion of both of the biometrics has several advantages such as increasing population coverage, deterring spoofing activities and reducing enrolment failure. In this doctoral dissertation, we make a first attempt to combine online signature and iris biometrics. We principally explore the fusion of iris and online signature biometrics and their potential application as biometric identifiers. To address this issue, investigations is carried out into the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. We compare the results of the multimodal approach with the results of the individual online signature and iris authentication approaches. This dissertation describes research into the feature and decision fusion levels in multimodal biometrics.
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Hasegawa, Robert Shigehisa. "Using synthetic images to improve iris biometric performance." Scholarly Commons, 2012. https://scholarlycommons.pacific.edu/uop_etds/827.

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Randolph, Adriane. "Individual-Technology Fit: Matching Individual Characteristics and Features of Biometric Interface Technologies with Performance." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/cis_diss/11.

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Abstract INDIVIDUAL-TECHNOLOGY FIT: MATCHING INDIVIDUAL CHARACTERISTICS AND FEATURES OF BIOMETRIC INTERFACE TECHNOLOGIES WITH PERFORMANCE By ADRIANE B. RANDOLPH MAY 2007 Committee Chair: Dr. Melody Moore Jackson Major Department: Computer Information Systems The term biometric literally means “to measure the body”, and has recently been associated with physiological measures commonly used for personal verification and security applications. In this work, biometric describes physiological measures that may be used for non-muscularly controlled computer applications, such as brain-computer interfaces. Biometric interface technology is generally targeted for users with severe motor disabilities which may last long-term due to illness or injury or short-term due to temporary environmental conditions. Performance with a biometric interface can vary widely across users depending upon many factors ranging from health to experience. Unfortunately, there is no systematic method for pairing users with biometric interface technologies to achieve the best performance. The current methods to accommodate users through trial-and-error result in the loss of valuable time and resources as users sometimes have diminishing abilities or suffer from terminal illnesses. This dissertation presents a framework and methodology that links user characteristics and features of biometric interface technologies with performance, thus expediting the technology-fit process. The contributions include an outline of the underlying components of capturing and representing individual user characteristics and the impact on the performance of basic interaction tasks using a methodology called biometric user profiling. In addition, this work describes a methodology for objectively measuring an individual’s ability to control a specific biometric interface technology such as one based on measures of galvanic skin response or neural activity. Finally, this work incorporates these concepts into a new individual-technology fit framework for biometric interface technologies stemming from literature on task-technology fit. Key words: user profiles, biometric user profiling, biometric interfaces, fit, individual-technology fit, galvanic skin response, functional near-infrared, brain-computer interface
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Verett, Marianna J. "Performance and usage of biometrics in a testbed environment for tactical purposes." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FVerett.pdf.

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Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, December 2006.
Thesis Advisor(s): Alex Bordetsky. "December 2006." Includes bibliographical references (p. 71-74). Also available in print.
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Mohanty, Pranab. "Learning from biometric distances : performance and security related issues in face recognition systems." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002298.

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El, Seuofi Sherif M. "Performance Evaluation of Face Recognition Using Frames of Ten Pose Angles." Youngstown State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1198184813.

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Randolph, Adriane B. "Individual-technology fit matching individual characteristics and features of biometric interface technologies with performance /." unrestricted, 2007. http://etd.gsu.edu/theses/available/etd-05182007-113229/.

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Thesis (Ph. D.)--Georgia State University, 2007.
Title from file title page. Melody Moore, committee chair; Detmar Straub, Veda Storey, Bruce Walker, committee members. Electronic text (166 p. : ill. (some col.)) : digital, PDF file. Description based on contents viewed Nov. 5, 2007. Includes bibliographical references (p. 160-164).
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Kannavara, Raghudeep. "DESIGN AND PERFORMANCE ANALYSIS OF A SECURE PROCES-SOR SCAN-SP WITH CRYPTO-BIOMETRIC CAPABILITIES." Wright State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=wright1254532768.

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Šmida, Vladimír. "Fingerprint Image Quality Assessment." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-237090.

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Kritickým prvkem biometrického systému pro rozpoznávání otisků prstů je proces snímání. Kvalita snímku totiž ovlivňuje všechny další části systému počínaje zpracováním obrazu, přes extrakci rysů až po samotné rozhodnutí. Přestože bylo navrženo několik metod určování kvality snímku, chybějící formální specifikace kvality otisku nedovoluje ověřit jejich přesnost. Tato diplomová práce se zabývá hodnocením metod určujících kvalitu biometrického signálu otisku prstu. Popisuje jednotlivé faktory ovlivňující kvalitu spolu se současnými přístupy používanými pro její odhad. V práci je rovněž vysvětlena evaluační technika navržená za účelem porovnání schopnosti jednotlivých metod předpovědět výkon biometrického systému. Několik metod pro odhad kvality bylo implementováno a ohodnoceno touto technikou.
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Ndlangisa, Mboneli. "DRUBIS : a distributed face-identification experimentation framework - design, implementation and performance issues." Thesis, Rhodes University, 2004. http://eprints.ru.ac.za/93/1/MNdlangisa-MSc.pdf.

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We report on the design, implementation and performance issues of the DRUBIS (Distributed Rhodes University Biometric Identification System) experimentation framework. The Principal Component Analysis (PCA) face-recognition approach is used as a case study. DRUBIS is a flexible experimentation framework, distributed over a number of modules that are easily pluggable and swappable, allowing for the easy construction of prototype systems. Web services are the logical means of distributing DRUBIS components and a number of prototype applications have been implemented from this framework. Different popular PCA face-recognition related experiments were used to evaluate our experimentation framework. We extract recognition performance measures from these experiments. In particular, we use the framework for a more indepth study of the suitability of the DFFS (Difference From Face Space) metric as a means for image classification in the area of race and gender determination.
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Books on the topic "Biometric performance"

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Elsworth, John T. Design and performance of biometric system. Hauppauge, N.Y: Nova Science Publishers, 2010.

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Schuckers, Michael E. Computational methods in biometric authentication: Statistical methods for performance evaluation. London: Springer, 2010.

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Petrovska-Delacrétaz, Dijana, Bernadette Dorizzi, and Gérard Chollet, eds. Guide to Biometric Reference Systems and Performance Evaluation. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84800-292-0.

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Comstock, James R. Mental-state estimation, 1987: Proceedings of a workshop sponsored by the National Aeronautics and Space Administration, Washington, D.C., and Old Dominion University, Norfolk, Virginia, and held in Williamsburg, Virginia, June 3-4, 1987. Washington, D.C: National Aeronautics and Space Administration, Scientific and Technical Information Division, 1988.

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Comstock, James R. Mental-state estimation, 1987: Proceedings of a workshop sponsored by the National Aeronautics and Space Administration, Washington, D.C., and Old Dominion University, Norfolk, Virginia, and held in Williamsburg, Virginia, June 3-4, 1987. Washington, D.C: National Aeonautics and Space Administration, Scientific and Technical Information Division, 1988.

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Comstock, James R. Mental-state estimation 1987: Proceedings of a workshop sponsored by the National Aeronautics and Space Administration, Washington, D.C., and Old Dominion University, Norfolk, Virginia, and held in Williamsburg, Virginia, June 3-4, 1987. Hampton, Va: Langley Research Center, 1988.

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United States. Government Accountability Office. Homeland security: Federal Protective Service could better measure the performance of its control centers : report to the Chairman, Committee on Government Reform, House of Representatives. Washington, D.C: U.S Government Accountability Office, 2006.

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(Editor), James Wayman, Anil Jain (Editor), Davide Maltoni (Editor), and Dario Maio (Editor), eds. Biometric Systems: Technology, Design and Performance Evaluation. Springer, 2004.

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James, Wayman, ed. Biometric systems: Technology, design and performance evaluation. London: Springer, 2005.

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Guide to Biometric Reference Systems and Performance Evaluation. Springer, 2009.

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Book chapters on the topic "Biometric performance"

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Ren, Chunxiao, Yilong Yin, and Yanbin Ning. "A Performance Improvement Method for Existing Fingerprint Systems." In Biometric Recognition, 120–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35136-5_15.

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Xian, Ran, and Wenxin Li. "Performance Evaluation of Finger Vein Verification Algorithms in PFVR2014." In Biometric Recognition, 244–51. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12484-1_27.

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Bourlai, Thirimachos, Kieron Messer, and Josef Kittler. "Performance versus Computational Complexity Trade-Off in Face Verification." In Biometric Authentication, 169–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_24.

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Liu, Shilei, Beining Huang, Yuankai Yu, and Wenxin Li. "Biometric Identification System’s Performance Enhancement by Improving Registration Progress." In Biometric Recognition, 288–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35136-5_35.

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El Abed, Mohamad, Romain Giot, Baptiste Hemery, Julien Mahier, and Christophe Rosenberger. "Performance Evaluation of Biometric Systems." In Signal and Image Processing for Biometrics, 207–30. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118561911.ch11.

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Lee, Tae-Seung, and Ho-Jin Choi. "High Performance Speaker Verification System Based on Multilayer Perceptrons and Real-Time Enrollment." In Biometric Authentication, 623–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_85.

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Nanavati, Samir, and Michael Thieme. "Ability to Verify: A Metric for System Performance in Real-World Comparative Biometric Testing." In Biometric Solutions, 393–409. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1053-6_15.

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Mason, James Eric, Issa Traoré, and Isaac Woungang. "Measured Performance." In Machine Learning Techniques for Gait Biometric Recognition, 175–88. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-29088-1_8.

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Lu, Jingting, Hui Ye, Wei Jia, Yang Zhao, Hai Min, Wenxiong Kang, and Bob Zhang. "A Performance Evaluation of Local Descriptors, Direction Coding and Correlation Filters for Palm Vein Recognition." In Biometric Recognition, 279–87. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46654-5_31.

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Ahuja, Mini Singh, and Sumit Chabbra. "Biometric Encryption: Combining Fingerprints and Cryptography." In High Performance Architecture and Grid Computing, 505–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22577-2_69.

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Conference papers on the topic "Biometric performance"

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Hube, Jens Peter. "Using Biometric Verification to Estimate Identification Performance." In 2006 Biometrics Symposium: Special Session on Research at the Biometric Consortium Conference. IEEE, 2006. http://dx.doi.org/10.1109/bcc.2006.4341620.

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Mansfield, T. "Performance testing of biometric systems." In IEE Colloquium on Visual Biometrics. IEE, 2000. http://dx.doi.org/10.1049/ic:20000464.

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De A. S. M., Juliana, and Márjory Da Costa-Abreu. "An evaluation of a three-modal hand-based database to forensic-based gender recognition." In Simpósio Brasileiro de Segurança da Informação e de Sistemas Computacionais. Sociedade Brasileira de Computação, 2019. http://dx.doi.org/10.5753/sbseg.2019.13989.

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In recent years, behavioural soft-biometrics have been widely used to improve biometric systems performance. Information like gender, age and ethnicity can be obtained from more than one behavioural modality. In this paper, we propose a multimodal hand-based behavioural database for gender recognition. Thus, our goal in this paper is to evaluate the performance of the multimodal database. For this, the experiment was realised with 76 users and was collected keyboard dynamics, touchscreen dynamics and handwritten signature data. Our approach consists of compare two-modal and one-modal modalities of the biometric data with the multimodal database. Traditional and new classifiers were used and the statistical Kruskal-Wallis to analyse the accuracy of the databases. The results showed that the multimodal database outperforms the other databases.
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Ibrahim, Dyala R., Abdelfatah A. Tamimi, and Ayman M. Abdalla. "Performance analysis of biometric recognition modalities." In 2017 8th International Conference on Information Technology (ICIT). IEEE, 2017. http://dx.doi.org/10.1109/icitech.2017.8079977.

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Saponara, Sergio. "Biometric performance measurements in combat sports." In 2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA). IEEE, 2016. http://dx.doi.org/10.1109/memea.2016.7533725.

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Li, Jing, Yongkang Wong, and Terence Sim. "Towards protecting biometric templates without sacrificing performance." In 2016 23rd International Conference on Pattern Recognition (ICPR). IEEE, 2016. http://dx.doi.org/10.1109/icpr.2016.7899771.

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Sacanamboy, Mayra, and Bojan Cukic. "Cost curve analysis of biometric system performance." In 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (BTAS). IEEE, 2009. http://dx.doi.org/10.1109/btas.2009.5339073.

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Schuckers, Michael E. "Theoretical statistical correlation for biometric identification performance." In ICASSP 2008 - 2008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2008. http://dx.doi.org/10.1109/icassp.2008.4518836.

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Olsen, Martin Aastrup, Marek Dusio, and Christoph Busch. "Fingerprint skin moisture impact on biometric performance." In 2015 International Workshop on Biometrics and Forensics (IWBF). IEEE, 2015. http://dx.doi.org/10.1109/iwbf.2015.7110223.

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Veldhuis, Raymond N. J. "The relation between the secrecy rate of biometric template protection and biometric recognition performance." In 2015 International Conference on Biometrics (ICB). IEEE, 2015. http://dx.doi.org/10.1109/icb.2015.7139055.

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Reports on the topic "Biometric performance"

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O'Toole, Alice J. Person Identification from Video with Multiple Biometric Cues: Benchmarks for Human and Machine Performance. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada415169.

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