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Author: S.Mohana Prakash
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 5
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Book Description
Biometrics is used to uniquely identify a person‘s individual based on physical and behavioural characteristics. Unimodal biometric system contains various problems such as degree of freedom, spoof attacks, non-universality, noisy data and error rates. Multimodal biometrics is introduced to overcome the limitations in Unimodal biometrics.
Author: S.Mohana Prakash
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 5
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Book Description
Biometrics is used to uniquely identify a person‘s individual based on physical and behavioural characteristics. Unimodal biometric system contains various problems such as degree of freedom, spoof attacks, non-universality, noisy data and error rates. Multimodal biometrics is introduced to overcome the limitations in Unimodal biometrics.
Author: Fawaz Alsaade
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: Waziha Kabir
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
In recent years, biometric-based authentication systems have become very important in view of their ability to prevent identity theft by identifying an individual with high accuracy and reliability. Multimodal biometric systems have now drawn some attention in view of their ability to provide a performance superior to that provided by the corresponding unimodal biometric systems by utilizing more than one biometric modality. The existing multimodal biometric systems fuse multiple modalities at a single level, such as sensor, feature, score, rank or decision, and no study to fuse the modalities at more than one level that may lead to a further improvement in the performance of multimodal biometric systems, has been hitherto undertaken. In this thesis, multimodal biometric systems, wherein fusions of the modalities are carried out at more than one level, are investigated. In order to improve the performance of multimodal biometric systems over unimodal biometric systems, normalization and weighting of scores from multiple matchers are essential tasks. In view of this, in the first part of the thesis, a number of normalization and weighting techniques under the score level fusion are investigated. Unlike the existing normalization techniques that are based only on the genuine scores, four new techniques based on both the genuine and impostor scores, are proposed. Two weighting techniques that are based on confidence of the scores, are proposed. Extensive experiments are conducted to evaluate the performance of the multimodal biometric system under the score-level fusion (MBS-SL) using the proposed normalization and weighting techniques. The focus of the second part of this thesis is on the development of multimodal biometric systems, wherein fusions of the modalities are carried out at multiple levels. Specifically, two multimodal biometric systems, in which three modalities are used for their fusion both at the feature level and the score level, are proposed. In the first multimodal biometric system, referred to as the multimodal biometric system with feature level and score level (MBS-FSL) fusions, the features of the three modalities are encoded using the binary hash encoding technique. Unlike the existing techniques for feature level fusion that use unencoded features, this encoding technique allows the neighbourhood feature information to be taken into account. The score-level fusion is carried out on the score obtained from the feature-level fusion and the score from the matching module of the modality that has the lowest equal error rate. In the proposed MBS-FSL, the border values of raw features could not participate in the encoding in view 4-connected neighbors not being available. In order to take both the border and non-border information as well as the neighbourhood information into consideration, a second multimodal biometric system, referred to as the multimodal biometric system with modified feature level and score level (MBS-MFSL) fusions, is proposed, wherein both the raw and encoded features are taken into account. In this system, the feature-level fusion is carried out in a manner similar to that for the MBS-FSL system. The score-level fusion is then carried out between the score obtained from the feature-level fusion, the score from the matching module of the modality that was not utilized in the feature-level fusion, and the scores from individual modalities by using their raw features. Extensive experiments are performed to evaluate the performance of the two proposed multimodal biometric systems. The results of these experiments demonstrate that both of the proposed multimodal biometric systems provide performance superior to that provided by the existing multimodal biometric systems in which fusion of modalities is carried out at a single level, namely, the score level. Experimental results also show that, in view of both the border and neighbourhood feature information being considered in the proposed MBS-MFSL system, it provides a performance superior to that provided by MBS-FSL system. The investigation undertaken in this thesis is aimed at advancing the present knowledge in the field of human biometric identification by considering, for the first time, the fusion of the modalities at two levels, namely, the feature and score levels, and it is hoped that the findings of this study would pave the way for further research in the development of new multimodal biometric systems employing fusion of modalities at multiple levels.
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: Arun A. Ross
Publisher: Springer Science & Business Media
ISBN: 0387331239
Category : Computers
Languages : en
Pages : 218
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Book Description
Details multimodal biometrics and its exceptional utility for increasingly reliable human recognition systems. Reveals the substantial advantages of multimodal systems over conventional identification methods.
Author: C. Chaw Poh
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Deepak Gupta
Publisher: Springer Nature
ISBN: 9811662851
Category : Technology & Engineering
Languages : en
Pages : 850
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Book Description
This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2021), held at Jan Wyzykowski University, Poland, during June 2021. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students.
Author: Massimo Tistarelli
Publisher: Springer Science & Business Media
ISBN: 3642017924
Category : Business & Economics
Languages : en
Pages : 1323
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Book Description
This book constitutes the refereed proceedings of the Third International Conference on Biometrics, ICB 2009, held in Alghero, Italy, June 2-5, 2009. The 36 revised full papers and 93 revised poster papers presented were carefully reviewed and selected from 250 submissions. Biometric criteria covered by the papers are assigned to face, speech, fingerprint and palmprint, multibiometrics and security, gait, iris, and other biometrics. In addition there are 4 papers on challenges and competitions that currently are under way, thus presenting an overview on the evaluation of biometrics.
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:
Publisher:
ISBN: 9781728164533
Category :
Languages : en
Pages :
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