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Intelligent Systems Reference Library

Cross Disciplinary Biometric Systems

Authors: Liu, Chengjun, Mago, Vijay Kumar

  • Latest research in Cross Disciplinary Biometric Systems
  • Includes applications to face recognition, iris recognition and fingerprint recognition
  • Written by leading experts in the field
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  • ISBN 978-3-642-28457-1
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About this book

Cross disciplinary biometric systems help boost the performance of the conventional systems. Not only is the recognition accuracy significantly improved, but also the robustness of the systems is greatly enhanced in the challenging environments, such as varying illumination conditions. By leveraging the cross disciplinary technologies, face recognition systems, fingerprint recognition systems, iris recognition systems, as well as image search systems all benefit in terms of recognition performance.  Take face recognition for an example, which is not only the most natural way human beings recognize the identity of each other, but also the least privacy-intrusive means because people show their face publicly every day. Face recognition systems display superb performance when they capitalize on the innovative ideas across color science, mathematics, and computer science (e.g., pattern recognition, machine learning, and image processing). The novel ideas lead to the development of new color models and effective color features in color science; innovative features from wavelets and statistics, and new kernel methods and novel kernel models in mathematics; new discriminant analysis frameworks, novel similarity measures, and new image analysis methods, such as fusing multiple image features from frequency domain, spatial domain, and color domain in computer science; as well as system design, new strategies for system integration, and different fusion strategies, such as the feature level fusion, decision level fusion, and new fusion strategies with novel similarity measures.

Table of contents (10 chapters)

  • Feature Local Binary Patterns

    Gu, Jiayu (et al.)

    Pages 1-13

  • New Color Features for Pattern Recognition

    Liu, Chengjun

    Pages 15-34

  • Gabor-DCT Features with Application to Face Recognition

    Liu, Zhiming (et al.)

    Pages 35-51

  • Frequency and Color Fusion for Face Verification

    Liu, Zhiming (et al.)

    Pages 53-71

  • Mixture of Classifiers for Face Recognition across Pose

    Liu, Chengjun

    Pages 73-92

Buy this book

eBook $139.00
price for USA (gross)
  • ISBN 978-3-642-28457-1
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.00
price for USA
  • ISBN 978-3-642-28456-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.00
price for USA
  • ISBN 978-3-642-42840-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Cross Disciplinary Biometric Systems
Authors
Series Title
Intelligent Systems Reference Library
Series Volume
37
Copyright
2012
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer Berlin Heidelberg
eBook ISBN
978-3-642-28457-1
DOI
10.1007/978-3-642-28457-1
Hardcover ISBN
978-3-642-28456-4
Softcover ISBN
978-3-642-42840-1
Series ISSN
1868-4394
Edition Number
1
Number of Pages
XVI, 228
Topics