Journal ArticleDOI
Multimodal Biometric Person Authentication : A Review
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TLDR
An overview of some performance parameters and error rates for biometric person authentication systems is presented, and the importance of information fusion in multi-biometric approach is considered.Abstract:
This paper provides a review of multimodal biometric person authentication systems. The paper begins with an introduction to biometrics, its advantages, disadvantages, and authentication system using them. A brief discussion on the selection criteria of different biometrics is also given. This is followed by a discussion on the classification of biometric systems, their strengths, and limitations. Detailed descriptions on the multimodal biometric person authentication system, different modes of operation, and integration scenarios are also provided. Considering the importance of information fusion in multi-biometric approach, a separate section is dedicated on the different levels of fusion, which include sensor-level, feature-level, score-level, rank-level, and abstract-level fusions, and also different rules of fusion. This paper also presents an overview of some performance parameters and error rates for biometric person authentication systems. A separate section is devoted to the recent trends...read more
Citations
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Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition
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ECG Authentication for Mobile Devices
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Overview of the combination of biometric matchers
Alessandra Lumini,Loris Nanni +1 more
TL;DR: Several systems and architectures related to the combination of biometric systems, both unimodal and multimodal, are overviews, classifying them according to a given taxonomy, and a case study for the experimental evaluation of methods for biometric fusion at score level is presented.
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Machine Learning in Automatic Speech Recognition: A Survey
TL;DR: A comprehensive review of common machine learning techniques like artificial neural networks, support vector machines, and Gaussian mixture models along with hidden Markov models employed in ASR is provided.
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Unimodal and Multimodal Biometric Sensing Systems: A Review
TL;DR: This paper discusses the stages involved in the biometric system recognition process and further discusses multimodal systems in terms of their architecture, mode of operation, and algorithms used to develop the systems.
References
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TL;DR: This is the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern recognition, and is designed as a text, with over 100 exercises, to benefit anyone involved in the fields of neural computation and pattern recognition.
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Suresh Kothari,Heekuck Oh +1 more
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An Algorithm for Vector Quantizer Design
Y. Linde,A. Buzo,Robert M. Gray +2 more
TL;DR: An efficient and intuitive algorithm is presented for the design of vector quantizers based either on a known probabilistic model or on a long training sequence of data.