› › An Approach For Full Reinforcement Based Biometric Score Fusion

An Approach for Full Reinforcement-based Biometric Score Fusion

Author : Mohamed Cheniti

Publisher : Infinite Study

Page : 13 pages

File Size : 50,56 MB

Release : 2024-01-01

Category : Business & Economics

ISBN :

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Book Description

Multibiometric systems have the potential to mitigate error rates and address certain inherent weaknesses found in unimodal systems. This study introduces an innovative scheme for user recognition in multibiometric systems, centered on a score-level fusion framework. The foundation of this framework lies in the full reinforcement operator (FRO), specifically estimating FRO through generator functions associated with triangular norms (T-norms and T-conorm). The efficiency of the proposed method has been showcased through an extensive set of experiments carried out on four commonly available benchmark databases: all three partitions of the National Institute of Standards and Technology (NIST) databases (Set 1, 2, 3), along with the XM2VTS database. Our method achieves superior accuracy compared to existing methods, reaching 100 % recognition on NIST-Set 1, 93.40 % on NIST-Set 2, and 94.54 % on the more challenging NIST-Set 3. The experimental findings illustrate that score fusion schemes based on FRO not only enhance verification rates when compared to current score-level fusion techniques (such as Asymmetric Aggregation Operators, Minimum, Maximum, T-norms, and Symmetric-Sum) but also offer a swift computational performance.



Framework for biometric match score fusion using statistical and belief models

Author : Mayank Vatsa

Publisher : Infinite Study

Page : 16 pages

File Size : 45,9 MB

Release :

Category :

ISBN :

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Book Description

This chapter presents a framework for multi-biometric match score fusion when non-ideal conditions cause conflict in the results of different unimodal biometrics classifiers. The proposed framework uses belief function theory to effectively fuse the match scores and density estimation technique to compute the belief assignments.





Multibiometric Systems

Author : Karthik Nandakumar

Publisher :

Page : 506 pages

File Size : 49,92 MB

Release : 2008

Category : Biometric identification

ISBN :

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Book Description

Multibiometric systems are gaining popularity because they are able to overcome limitations such as non-universality, noisy sensor data and susceptibility to spoof attacks common in unibiometric systems. We address two critical issues in the design of a multibiometric system, namely, fusion methodology and template security. We propose a fusion methodology based on the Neyman-Pearson theorem for combination of match scores provided by multiple biometric matchers. The likelihood ratio (LR) test used in the Neyman-Pearson theorem directly maximizes the genuine accept rate (GAR) at any desired false accept rate (FAR). We extend the likelihood ratio based fusion scheme to incorporate the quality of the biometric samples. The LR framework can be used for designing sequential multibiometric systems by constructing a binary decision tree classifier based on the marginal likelihood ratios of the individual matchers. The use of image quality information further improves the GAR to 90% at a FAR of 0:001%. Next, we show that the proposed likelihood ratio based fusion framework is also applicable to a multibiometric system operating in the identification mode. We investigate rank level fusion strategies and propose a hybrid scheme that utilizes both ranks and scores to perform fusion in the identification scenario. Fusion of multiple biometric sources requires storage of multiple templates for the same user corresponding to the individual biometric sources. Template security is an important issue because stolen biometric templates cannot be revoked. We propose a scheme for securing multibiometric templates as a single entity using the fuzzy vault framework. We have developed fully automatic implementa- tions of a ngerprint-based fuzzy vault that secures minutiae templates and an iris cryptosystem that secures iris code templates. We also demonstrate that a multibiometric vault achieves better recognition performance and higher security compared to a unibiometric vault.



Biometric Authentication

Author : Sun Yuan Kung

Publisher : Prentice Hall

Page : 504 pages

File Size : 39,87 MB

Release : 2005

Category : Computers

ISBN :

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Book Description

A breakthrough approach to improving biometrics performanceConstructing robust information processing systems for face and voice recognitionSupporting high-performance data fusion in multimodal systemsAlgorithms, implementation techniques, and application examples Machine learning: driving significant improvements in biometric performance As they improve, biometric authentication systems are becoming increasingly indispensable for protecting life and property. This book introduces powerful machine learning techniques that significantly improve biometric performance in a broad spectrum of application domains. Three leading researchers bridge the gap between research, design, and deployment, introducing key algorithms as well as practical implementation techniques. They demonstrate how to construct robust information processing systems for biometric authentication in both face and voice recognition systems, and to support data fusion in multimodal systems. Coverage includes: How machine learning approaches differ from conventional template matchingTheoretical pillars of machine learning for complex pattern recognition and classificationExpectation-maximization (EM) algorithms and support vector machines (SVM)Multi-layer learning models and back-propagation (BP) algorithmsProbabilistic decision-based neural networks (PDNNs) for face biometricsFlexible structural frameworks for incorporating machine learning subsystems in biometric applicationsHierarchical mixture of experts and inter-class learning strategies based on class-based modular networksMulti-cue data fusion techniques that integrate face and voice recognitionApplication case studies



Multimodal Biometric and Machine Learning Technologies

Author : Sandeep Kumar

Publisher : John Wiley & Sons

Page : 340 pages

File Size : 40,57 MB

Release : 2023-11-30

Category : Computers

ISBN : 1119785405

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Book Description

MULTIMODAL BIOMETRIC AND MACHINE LEARNING TECHNOLOGIES With an increasing demand for biometric systems in various industries, this book on multimodal biometric systems, answers the call for increased resources to help researchers, developers, and practitioners. Multimodal biometric and machine learning technologies have revolutionized the field of security and authentication. These technologies utilize multiple sources of information, such as facial recognition, voice recognition, and fingerprint scanning, to verify an individual???s identity. The need for enhanced security and authentication has become increasingly important, and with the rise of digital technologies, cyber-attacks and identity theft have increased exponentially. Traditional authentication methods, such as passwords and PINs, have become less secure as hackers devise new ways to bypass them. In this context, multimodal biometric and machine learning technologies offer a more secure and reliable approach to authentication. This book provides relevant information on multimodal biometric and machine learning technologies and focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity. The book provides content on the theory of multimodal biometric design, evaluation, and user diversity, and explains the underlying causes of the social and organizational problems that are typically devoted to descriptions of rehabilitation methods for specific processes. Furthermore, the book describes new algorithms for modeling accessible to scientists of all varieties. Audience Researchers in computer science and biometrics, developers who are designing and implementing biometric systems, and practitioners who are using biometric systems in their work, such as law enforcement personnel or healthcare professionals.



Biometric Systems

Author : James L. Wayman

Publisher : Springer Science & Business Media

Page : 380 pages

File Size : 14,45 MB

Release : 2005-09-20

Category : Computers

ISBN : 1846280648

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Book Description

Biometric Systems provides practitioners with an overview of the principles and methods needed to build reliable biometric systems. It covers three main topics: key biometric technologies, design and management issues, and the performance evaluation of biometric systems for personal verification/identification. The four most widely used technologies are focused on - speech, fingerprint, iris and face recognition. Key features include: in-depth coverage of the technical and practical obstacles which are often neglected by application developers and system integrators and which result in shortfalls between expected and actual performance; and protocols and benchmarks which will allow developers to compare performance and track system improvements.



Advanced Biometric Technologies

Author : Girija Chetty

Publisher : BoD – Books on Demand

Page : 398 pages

File Size : 50,42 MB

Release : 2011-08-09

Category : Computers

ISBN : 9533074876

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Book Description

The methods for human identity authentication based on biometrics - the physiological and behavioural characteristics of a person have been evolving continuously and seen significant improvement in performance and robustness over the last few years. However, most of the systems reported perform well in controlled operating scenarios, and their performance deteriorates significantly under real world operating conditions, and far from satisfactory in terms of robustness and accuracy, vulnerability to fraud and forgery, and use of acceptable and appropriate authentication protocols. To address some challenges, and the requirements of new and emerging applications, and for seamless diffusion of biometrics in society, there is a need for development of novel paradigms and protocols, and improved algorithms and authentication techniques. This book volume on "Advanced Biometric Technologies" is dedicated to the work being pursued by researchers around the world in this area, and includes some of the recent findings and their applications to address the challenges and emerging requirements for biometric based identity authentication systems. The book consists of 18 Chapters and is divided into four sections namely novel approaches, advanced algorithms, emerging applications and the multimodal fusion. The book was reviewed by editors Dr. Girija Chetty and Dr. Jucheng Yang We deeply appreciate the efforts of our guest editors: Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers.



Data Fusion in Information Retrieval

Author : Shengli Wu

Publisher : Springer Science & Business Media

Page : 234 pages

File Size : 34,84 MB

Release : 2012-04-05

Category : Technology & Engineering

ISBN : 3642288669

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Book Description

The technique of data fusion has been used extensively in information retrieval due to the complexity and diversity of tasks involved such as web and social networks, legal, enterprise, and many others. This book presents both a theoretical and empirical approach to data fusion. Several typical data fusion algorithms are discussed, analyzed and evaluated. A reader will find answers to the following questions, among others: What are the key factors that affect the performance of data fusion algorithms significantly? What conditions are favorable to data fusion algorithms? CombSum and CombMNZ, which one is better? and why? What is the rationale of using the linear combination method? How can the best fusion option be found under any given circumstances?



Biometric Recognition

Author : National Research Council

Publisher : National Academies Press

Page : 182 pages

File Size : 48,3 MB

Release : 2010-12-12

Category : Computers

ISBN : 0309142075

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Book Description

Biometric recognition-the automated recognition of individuals based on their behavioral and biological characteristic-is promoted as a way to help identify terrorists, provide better control of access to physical facilities and financial accounts, and increase the efficiency of access to services and their utilization. Biometric recognition has been applied to identification of criminals, patient tracking in medical informatics, and the personalization of social services, among other things. In spite of substantial effort, however, there remain unresolved questions about the effectiveness and management of systems for biometric recognition, as well as the appropriateness and societal impact of their use. Moreover, the general public has been exposed to biometrics largely as high-technology gadgets in spy thrillers or as fear-instilling instruments of state or corporate surveillance in speculative fiction. Now, as biometric technologies appear poised for broader use, increased concerns about national security and the tracking of individuals as they cross borders have caused passports, visas, and border-crossing records to be linked to biometric data. A focus on fighting insurgencies and terrorism has led to the military deployment of biometric tools to enable recognition of individuals as friend or foe. Commercially, finger-imaging sensors, whose cost and physical size have been reduced, now appear on many laptop personal computers, handheld devices, mobile phones, and other consumer devices. Biometric Recognition: Challenges and Opportunities addresses the issues surrounding broader implementation of this technology, making two main points: first, biometric recognition systems are incredibly complex, and need to be addressed as such. Second, biometric recognition is an inherently probabilistic endeavor. Consequently, even when the technology and the system in which it is embedded are behaving as designed, there is inevitable uncertainty and risk of error. This book elaborates on these themes in detail to provide policy makers, developers, and researchers a comprehensive assessment of biometric recognition that examines current capabilities, future possibilities, and the role of government in technology and system development.