Error Rate Equations General Biometric System
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Request full-text Error rate equations for the general biometric systemArticle in IEEE Robotics & Automation Magazine 6(1):35 - 48 · April 1999 with 22 ReadsDOI: 10.1109/100.755813 · Source: IEEE Xplore1st James L. WaymanAbstractWe derive equations for false-match and false-nonmatch error-rate prediction for the general M-to-N biometric identification system, under the simplifying, but limiting, assumption of statistical independence of all errors. For http://ieeexplore.ieee.org/iel4/100/16385/00755813.pdf systems with large N, error rates are shown to be linked to the hardware processing speed through the system penetration coefficient and the throughput equation. These equations are somewhat limited in their ability to handle sample-dependent decision policies and are shown to be consistent with https://www.researchgate.net/publication/3344549_Error_rate_equations_for_the_general_biometric_system previously published cases for verification and identification. Applying parameters consistent with the Philippine Social Security System benchmark test results for AFIS vendors, we establish that biometric identification systems can be used in populations of 100 million people. Development of more generalized equations, accounting for error correlation and general sample-dependent thresholds, establishing confidence bounds, and substituting the inter-template for the impostor distribution under the template generating policy remain for future studyDo you want to read the rest of this article?Request full-text CitationsCitations70ReferencesReferences15On the Effectiveness of Sensor-enhanced Keystroke Dynamics Against Statistical Attacks"Measuring the accuracy of a biometric identification system is a well-studied problem [32]. Briefly, the performance of a system is characterized by two metrics: @BULLET False Match Rate (FMR), which expresses the number of impostors accepted as legitimate users; @BULLET False Nonmatch Ra
von GoogleAnmeldenAusgeblendete FelderBooksbooks.google.de - This book provides ample coverage of theoretical and experimental state-of-the-art work as well as new trends and directions in the https://books.google.com/books?id=o_51_lH4Ee0C&pg=PA270&lpg=PA270&dq=error+rate+equations+general+biometric+system&source=bl&ots=1o5GKP3Oh5&sig=LfY8lAciiSMOmzf-BCPOuXQLkmQ&hl=en&sa=X&ved=0ahUKEwisnqrvvNLPAhUFcD4KHYXBA4o biometrics field. It offers students and software engineers a thorough understanding of how some core low-level building blocks of a multi-biometric system are implemented....https://books.google.de/books/about/Face_Biometrics_for_Personal_Identificat.html?hl=de&id=o_51_lH4Ee0C&utm_source=gb-gplus-shareFace Biometrics for Personal IdentificationMeine BücherHilfeErweiterte BuchsucheE-Book kaufen - 91,62 €Nach Druckexemplar suchenSpringer ShopAmazon.deBuch.deBuchkatalog.deLibri.deWeltbild.deIn Bücherei suchenAlle Händler»Face Biometrics for Personal Identification: Multi-Sensory Multi-Modal SystemsBesma Abidi, error rate Mongi A. AbidiSpringer Science & Business Media, 08.04.2007 - 275 Seiten 0 Rezensionenhttps://books.google.de/books/about/Face_Biometrics_for_Personal_Identificat.html?hl=de&id=o_51_lH4Ee0CThis book provides ample coverage of theoretical and experimental state-of-the-art work as well as new trends and directions in the biometrics field. It offers students and software engineers a thorough understanding of how some core low-level error rate equations building blocks of a multi-biometric system are implemented. While this book covers a range of biometric traits, its main emphasis is placed on multi-sensory and multi-modal face biometrics algorithms and systems. Voransicht des Buches » Was andere dazu sagen-Rezension schreibenEs wurden keine Rezensionen gefunden.Ausgewählte SeitenTitelseiteInhaltsverzeichnisIndexVerweiseInhaltIntroduction 1 Recognizing Faces Across Age Progression 26 3 35 Quality Assessment and Restoration of Face Images 43 A ShiftInvariant Principal Component Analysis PCA 61 Towards Person Authentication by Fusing Visual and Thermal 73 4 79 Feature Selection for Improved Face Recognition 109 3D Face and Ear Recognition? 139 Human Recognition at a Distance in Video by Integrating 165 Fusion Techniques in Multibiometric Systems 185 Performance Prediction Methodology for Multibiometric Systems 213 Acknowledgments 231 229 References 247 Index 272 Urheberrecht MehrMultimodal Face and Speaker Identification 123 WenigerAndere Ausgaben - Alle anzeigenFace Biometrics for Personal Identification: Multi-Sensory Multi-Modal Systems