融合2DDCT、2DPCA和2DLDA的人脸识别方法

摘要

二维主分量分析(2DPCA)是人脸识别中的一种非常有效的特征提取方法.二维线性判别(2DLDA)方法具有很好的分类效果.在研究这两种理论的基础上提出一种基于2DDCT(二维离散余弦变换)与2DPCA+ 2DLDA相结合的人脸识别方法,并在0RL人脸库上分别对单一的方法与相融合的方法进行识别比较研究.实验结果表明,提出的方法不仅提高了识别率,而且减少了训练与分类时间.%Two-dimensional principal component analysis (2DPCA) is a very effective feature extraction method in face recognition; two-dimensional linear discriminant (2DLDA) method has very good classification results. In this paper, based on the study of these two theories, we propose a new face recognition method which is on the basis of integrating the two-dimensional discrete cosine transform (2DDCT) with 2DPCA and 2DLDA, and utilising the ORL database we carry out respectively the comparative study on recognitions with each single method and the integrated method. Experimental results show that the integrated method proposed in the paper improves the recognition rate, and it also reduces the training and classification time as well.