摘要
提出一种基于Gabor小波特征的综合判别函数(SDF)匹配滤波器人脸识别方法.该方法选用具有代表性的人脸训练库,在Gabor特征空间上生成相应的SDF匹配滤波器;每幅测试图像在这些非正交向量的投影可以生成一组相关特征向量,用两个相关特征向量的距离来衡量不同人脸图像之间的相似度.Gabor变换、SDF匹配滤波器和类别特征分析法的采用,使得该方法对光照变化、表情变化等因素具有良好的鲁棒性,并具有良好的推广性.基于FERET人脸测试库的对比实验结果验证了该方法的有效性.
A novel face recognition method is proposed based on synthetic discriminant function （SDF） matched filters using Gabor wavelet features. In this method, the generic training face database is used, and the corresponding SDF matched filters are generated in the Gabor feature space. Each test image is projected onto those non-orthogonal basis vectors to yield a group of correlative eigenvectors, and the similarity between two face images is measured using the distance between the corresponding eigenvectors. The adoption of Gabor transform, SDF matched filter and class-dependence feature analysis （CFA） enables the proposed method to be robust to the variations of illumination and expression. In addition, this method is of good generalizability. Experimental comparison on FERET face database verifies the validity of the proposed method.
出处
《信息与控制》
CSCD
北大核心
2008年第5期633-636,共4页
Information and Control
关键词
人脸识别
小波变换
综合判别函数
face recognition
wavelet transform
synthetic discriminant function
