基于EHMM-SVM的人脸识别算法研究

A face recognition algorithm based on EHMM-SVM

EHMM依靠输出最大相似概率来判定人脸,但由于人脸图像的相似性,此方法可能会导致识别错误。对此,提出了一种基于EHMM-SVM的人脸识别方法。运用二维离散余弦变换(2D-DCT)进行人脸特征提取,得到观察向量序列。通过双重嵌套Viterbi算法求出每个人脸图像对应EHMM模型的输出概率,把输出概率输入SVM中进行分类训练以及识别测试,得到人脸识别的结果。运用ORL和YALE人脸数据库进行实验。实验结果表明了该方法的可行性及有效性。

The EHMM relies on the output maximum likelihood probability to determine the face im- age. However, because of the similarity between face images, this method can lead to recognition er- rors. We propose a face recognition method based on the EHMM-SVM. The two-dimensional discrete cosine transform （2D-DCT） is used to extract face features so as to obtain the observation vector se- quence. The output probability of each face image corresponding to the EHMM model is obtained by the double nested Viterbi algorithm. The output probability is input into the SVM for classification training and recognition tests, and the results of face recognition are obtained. ORL and YALE face databases are used in the experiments. Experimental results show the feasibility and effectiveness of the method.