关键词: 人脸识别, Gabor滤波, Gabor定向模式, 特征提取

Abstract: In order to extract more effective classification features from the Gabor filtered maps, a novel face recognition method based on GDP（Gabor Directional Pattern） is proposed. Firstly, multi-scale and multi-orientation Gabor filters are used to extract their corresponding Gabor magnitude maps. Then, a novel operator named GDP is proposed, which converts the Gabor transformed images into several GDP maps by encoding all the Gabor magnitude maps with the same scale. Finally the spatial histograms of all the GDP maps are concatenated together to represent the facial appearances. The extracted GDP feature not only has good robustness but also has low dimensionality. Experimental results on the ORL and CAS-PEAL databases show that the performance of proposed method is superior to other Gabor based methods such as LGBP（Local Gabor Binary Pattern）and LGXP（Local Gabor XOR Pattern） with a significantly lower feature dimension.

Key words: face recognition, Gabor filter, Gabor Directional Pattern（GDP）, feature extraction