tailieunhanh - Báo cáo hóa học: "Research Article Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 469109 8 pages doi 2008 469109 Research Article Kernel Learning of Histogram of Local Gabor Phase Patterns for Face Recognition Baochang Zhang 1 Zongli Wang 2 and Bineng Zhong3 1 School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics Beijing 100080 China 2 Computer Science and Engineering Beijing Institute of Technology Beijing 100080 China 3 Computer College Harbin Institute of Technology Harbin 150001 China Correspondence should be addressed to Baochang Zhang bczhang@ Received 27 August 2007 Revised 15 January 2008 Accepted 4 February 2008 Recommended by Hubert Cardot This paper proposes a new face recognition method named kernel learning of histogram of local Gabor phase pattern K-HLGPP which is based on Daugman s method for iris recognition and the local XOR pattern LXP operator. Unlike traditional Gabor usage exploiting the magnitude part in face recognition we encode the Gabor phase information for face classification by the quadrant bit coding QBC method. Two schemes are proposed for face recognition. One is based on the nearest-neighbor classifier with chi-square as the similarity measurement and the other makes kernel discriminant analysis for HLGPP K-HLGPP using histogram intersection and Gaussian-weighted chi-square kernels. The comparative experiments show that K-HLGPP achieves a higher recognition rate than other well-known face recognition systems on the large-scale standard FERET FERET200 and CAS-PEAL-R1 databases. Copyright 2008 Baochang Zhang et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION A good object representation or pattern representation is one of the key issues for a well-designed pattern .