Face Recognition Based on Color Gabor Features
基于彩色Gabor特征的人脸识别技术

In this paper a method which can improve the performance of face recognition system using color Gabor features is presented.First,quaternion is used to describe the color information,considering that Gabor filters have desirable characteristics of spatial locality and orientation selectivity,and they are extended to quaternion space.Then utilizing the convolution of the key points and the Gabor filters to extract features,by doing this the gray Gabor features are extended to the color ones.In the end,for the extracted features,we used PCA for dimension reduction and SVM for recognition.The experiment carried on Color FERET Database and the result utilizing ROC curve for cross-validation show that the use of color texture information can improve the efficiency of face recognition system markedly.