基于I-DCV的人脸识别方法

Face recognition method based on I-DCV

在人脸识别的过程中,利用独立成分分析(ICA)方法得到的特征能够很好的描述原始图像,但是不具备很好的判别分类能力。判别共同矢量(DCV)是一种在类内散布矩阵的零空间中求取投影矩阵的方法,相比线性鉴别分析(LDA)方法,可以得到更具鉴别能力的特征。因此本文提出一种新的特征提取算法,简称I-DCV,首先对预处理后的人脸图像应用独立成分分析算法去除二阶及高阶冗余信息,然后利用DCV对求取的独立特征向量作进一步的处理,最后依据欧式距离进行分类识别。实验结果表明,本文提出的方法具有很好的识别性能。

During the face recognition, the features extracted by Independent Component Analysis （ICA） can ob- tain a good description of the original image, but they can not represent the category information perfectly. Discrim- inate Common Vector （DCV） is the method which calculates the projection matrix in the zero space of within-class scatter matrix. Compared with the Linear Discriminate Analysis （LDA） method, DCV can get more discriminating features. Therefore, a new feature extraction algorithm called I-DCV is proposed. Firstly, by using ICA in prepro- cessed face images, the redundant information in second-order and higher-order can be removed. Then the obtained independent feature vector is processed by the DCV algorithm for further processing. Finally, the Euclidean dis- tance is used for classification. Experimental results show that the proposed method has a good recognition perform- ance.