关键词: 人脸识别, 韦伯梯度方向直方图, 差动激励, 最近邻分类器

Abstract: To overcome the limitations of the traditional face recognition methods under variations in posture, expression and illumination, a method of face recognition based on Histograms of Weber Oriented Gradient（HWOG） is proposed. Differential excitation operator is firstly adopted to extract the structure and texture features of an image. Then the edge features of original image are extracted by using HOG operator. HWOG feature maps are divided into several blocks, and the concatenated histogram features calculated over all blocks is used for the feature descriptor of face recognition. Finally, the recognition is performed by using the nearest neighbor classifier. Experimental results on YALE, ORL, CAS-PEAL-R1 face databases demonstrate that proposed descriptor is effective, and also robust to variations of position, expression and illumination.

Key words: face recognition, Histograms of Weber Oriented Gradient（HWOG）, differential excitation, nearest neighbor classifier