Discriminative Learning in Biometrics

Springer | Image Processing | Nov. 22 2016 | ISBN-10: 9811020558 | 266 Pages | PDF | 7.68 mb

Authors: Zhang, David, Xu, Yong, Zuo, Wangmeng
Summarizes the latest studies on discriminative learning methods and their applications to biometric recognition
Covers different biometric recognition technologies, including face recognition, palmprint authentication, and multi-biometrics
Provides numerous executive procedures in addition to text presentation of the novel algorithms, technical schemes and insightful strategies
Written by one of the 2014 ISI Highly Cited Researchers and pioneers of biometrics research

This monograph describes the latest advances in discriminative learning methods for biometric recognition. Specifically, it focuses on three representative categories of methods: sparse representation-based classification, metric learning, and discriminative feature representation, together with their applications in palmprint authentication, face recognition and multi-biometrics. The ideas, algorithms, experimental evaluation and underlying rationales are also provided for a better understanding of these methods. Lastly, it discusses several promising research directions in the field of discriminative biometric recognition.

Number of Pages
XIII, 266
Number of Illustrations and Tables
37 b/w illustrations, 73 illustrations in colour
Topics
Biometrics
Pattern Recognition

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