In order to solve the problem caused by variation illumination in human face recognition,we bring forward a face recognition algorithm based on the improved multi-sample. In this algorithm,the face image is processed ...In order to solve the problem caused by variation illumination in human face recognition,we bring forward a face recognition algorithm based on the improved multi-sample. In this algorithm,the face image is processed with Retinex theory,meanwhile,the Gabor filter is adopted to perform the feature extraction. The experimental results show that the application of Retinex theory improves the recognition accuracy,and makes the algorithm more robust to the variation illumination. The Gabor filter is more effective and accurate for extracting more useable facial local features. It is proved that the proposed algorithm has good recognition accuracy and it is stable under variation illumination.展开更多
基金Sponsored by the Science and Technology Research Projects in Office of Education in Heilongjiang Province(Grant No. 11531034)the Natural Science Fund in Heilongjiang Province(Grant No. F2007-13)the Heilongjiang Postdoctoral Science Foundation (Grant No. LBH-Z06054)
文摘In order to solve the problem caused by variation illumination in human face recognition,we bring forward a face recognition algorithm based on the improved multi-sample. In this algorithm,the face image is processed with Retinex theory,meanwhile,the Gabor filter is adopted to perform the feature extraction. The experimental results show that the application of Retinex theory improves the recognition accuracy,and makes the algorithm more robust to the variation illumination. The Gabor filter is more effective and accurate for extracting more useable facial local features. It is proved that the proposed algorithm has good recognition accuracy and it is stable under variation illumination.
