Unification of Evidence Theoretic Fusion Algorithms: A Case Study in Level-2 and Level-3 Fingerprint Features PDF Download
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Author: Mayank Vatsa
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
This paper formulates an evidence-theoretic multimodal unification approach using belief functions that takes into account the variability in biometric image characteristics. While processing non-ideal images the variation in the quality of features at different levels of abstraction may cause individual classifiers to generate conflicting genuine-impostor decisions. Existing fusion approaches are non-adaptive and do not always guarantee optimum performance improvements.
Author: Mayank Vatsa
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
This paper formulates an evidence-theoretic multimodal unification approach using belief functions that takes into account the variability in biometric image characteristics. While processing non-ideal images the variation in the quality of features at different levels of abstraction may cause individual classifiers to generate conflicting genuine-impostor decisions. Existing fusion approaches are non-adaptive and do not always guarantee optimum performance improvements.
Author: Florentin Smarandache, Jean Dezert
Publisher: Infinite Study
ISBN: 1599733242
Category :
Languages : en
Pages : 506
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Book Description
The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions (see List of Articles published in this book, at the end of the volume) have been published or presented after disseminating the third volume (2009, http://fs.gallup.unm.edu/DSmT-book3.pdf) ininternational conferences, seminars, workshops and journals.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 506
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Book Description
The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions have been published or presented after disseminating the third volume (2009, http://fs.gallup.unm.edu/DSmT-book3.pdf) in international conferences, seminars, workshops and journals.
Author: David Zhang
Publisher: Springer
ISBN: 3319615459
Category : Technology & Engineering
Languages : en
Pages : 336
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Book Description
This book describes a range of new biometric technologies, such as high-resolution fingerprint, finger-knuckle-print, multi-spectral backhand, 3D fingerprint, tongueprint, 3D ear, and multi-spectral iris technologies. Further, it introduces readers to efficient feature extraction, matching and fusion algorithms, in addition to developing potential systems of its own. These advanced biometric technologies and methods are divided as follows: 1. High-Resolution Fingerprint Recognition; 2. Finger-Knuckle-Print Verification; 3. Other Hand-Based Biometrics; and 4. New Head-Based Biometrics. Traditional biometric technologies, such as fingerprint, face, iris, and palmprint, have been extensively studied and addressed in many research books. However, all of these technologies have their own advantages and disadvantages, and there is no single type of biometric technology that can be used for all applications. Many new biometric technologies have been developed in recent years, especia lly in response to new applications. The contributions gathered here focus on how to develop a new biometric technology based on the requirements of essential applications, and how to design efficient algorithms that yield better performance.
Author: Yingzi (Eliza) Du
Publisher: CRC Press
ISBN: 9814310883
Category : Computers
Languages : en
Pages : 328
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Book Description
This book introduces readers to the basic concepts, classical approaches, and the newest design, development, and applications of biometrics. It also provides a glimpse of future designs and research directions in biometrics. In addition, it discusses some latest concerns and issues in this area. Suitable for a wide range of readers, the book explains professional terms in plain English. Some concepts and designs discussed are so new that commercial systems based on them may not arrive in the market in the next 10 to 20 years.
Author: Stan Z. Li
Publisher: Springer Science & Business Media
ISBN: 0387730028
Category : Computers
Languages : en
Pages : 1466
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Book Description
With an A–Z format, this encyclopedia provides easy access to relevant information on all aspects of biometrics. It features approximately 250 overview entries and 800 definitional entries. Each entry includes a definition, key words, list of synonyms, list of related entries, illustration(s), applications, and a bibliography. Most entries include useful literature references providing the reader with a portal to more detailed information.
Author: Yi Chen (Data scientist)
Publisher:
ISBN:
Category : Fingerprints
Languages : en
Pages : 430
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Book Description
Author: Nalini Ratha
Publisher: Springer Science & Business Media
ISBN: 0387955933
Category : Computers
Languages : en
Pages : 466
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Book Description
An authoritative survey of intelligent fingerprint-recognition concepts, technology, and systems is given. Editors and contributors are the leading researchers and applied R&D developers of this personal identification (biometric security) topic and technology. Biometrics and pattern recognition researchers and professionals will find the book an indispensable resource for current knowledge and technology in the field.
Author: Karthik Nandakumar
Publisher:
ISBN:
Category : Biometric identification
Languages : en
Pages : 506
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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.
Author: David Hall
Publisher: CRC Press
ISBN: 1420038540
Category : Technology & Engineering
Languages : en
Pages : 564
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Book Description
The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut
