基于Gabor特征和EHMM的人脸识别方法

针对传统人脸识别方法在受到表情、姿态和光照等影响时存在鲁棒性差的问题,提出了一种改进的人脸识别方法.在特征提取上,该方法首先提取人脸的Gabor特征,接着利用DCT(discrete cosinetransform)压缩使得相似特征得到聚合,最后利用PCA(principal component analysis)分别...

Face recognition based on Gabor feature and EHMM

This paper brings forward a new face recognition method, aiming at improving the inefficient robustness of the traditional face recognition method when factors like expression, gesture, and illumination are involved. When it comes to feature extraction, this new method will first extract the Gabor feature of a human face, and then assemble the similar features with DCT(discrete cosine transform), and last, sieve out the DCT coefficients which can mostly represent each areas of human face with PCA(principal component analysis). When it comes to recognition method, it adapts EHMM (embedded hidden markov model), and improves the EHMM human face model according to the understanding of cognitive structure of human face. Comparative experiments show that the proposed method has a high recognition rate and a low complex rate. And it has excellent robustness, which proves that it can be easily applied to engineering projects.