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Intelligent Systems Reference Library #37: Cross Disciplinary Biometric Systemsby Chengjun Liu
Synopses & Reviews
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.
This book spans current progress in biometric systems including face recognition, fingerprint recognition, iris recognition and image search systems, connecting them to each other and to progress in color and pattern analysis, mathematics and computer science.
Table of Contents
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.
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