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《Acta Photonica Sinica》 2011-04
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An Adaptive Feature and Weight Selection Method Based on Gabor Image for Face Recognition

LIU Zhong-hua1,2,YIN Jun1,JIN Zhong1(1 School of Computer Science & Technology,Nanjing University of Science and Technology,Nanjing 210094,China)(2 Electronic Information Engineering College,Henan University of Science and Technology,Luoyang,Henan 471003,China)  
To overcome the negative effect of factors such as illumination and expression on face recognition,an adaptive feature and weight selection method was proposed.The method was based on Gabor image for face recognition.Firstly,40 independent feature matrices which were reconstructed with the same scale and the same direction transform results of the different face images were obtained by regarding every Gabor wavelet transformed output image as an independent sample.In order to enhance the robustness to facial expression and illumination variations,the contribution of each new feature matrix could be adaptively computed by the proposed adaptive weight method.Secondly,after applying discrete cosine transform to each feature matrix,the coefficients which had more power to discriminate different classes than others were selected by discrimination power analysis to construct feature vectors.And,linear discriminant analysis features were extracted to fulfill recognition task.Experiments on the face databases demonstrate the effectiveness of the proposed method.
【Fund】: 国家自然科学基金(No.60973098 No.60632050 No.60873151)资助
【CateGory Index】: TP391.41
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