Cross Disciplinary Biometric Systems. 1st ed. 2012

種類:

電子ブック

責任表示:

by Chengjun Liu, Vijay Kumar Mago

出版情報:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012

著者名:

• Liu, Chengjun.
• Mago, Vijay Kumar.
• SpringerLink (Online service)

シリーズ名:

Intelligent Systems Reference Library ; 37

ISBN:

9783642284571 [3642284574]    

注記:

Feature Local Binary Patterns -- New Color Features for Pattern Recognition -- Gabor-DCT Features with Application to Face Recognition -- Frequency and Color Fusion for Face Verification -- Mixture of Classifiers for Face Recognition Across Pose -- Wavelet Features for 3D Face Recognition -- Minutiae-based Fingerprint Matching -- Iris segmentation: state of the art and innovative methods -- Various Discriminatory Features for Eye Detection -- LBP and Color Descriptors for Image Classification.
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 c

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