摘要
首先分析了DCT用于特征降维的可行性,并给出了DCT特征降维的基本原理.然后以人脸识别和人脸表情识别为背景,在DCT和2DPCA具有相当的降维效果时,给出了DCT比2DPCA具有较高的人脸识别率和人脸表情识别率的理论分析.最后,利用AT&T人脸库和JAFFE人脸表情库,分别对DCT和2DPCA进行了比较仿真实验.
The feasibility of DCT to be used in image feature dimension reduction is analyzed, and the basic principle of the image feature dimension reduction based on DCT is given in this paper. And then, taking the face recognition and the facial expression recognition as the research background, the theoretical analysis that DCT algorithm has the higher recognition than 2DPCA（two-dimensional principal component analysis）in the face recognition and the facial expression recognition is given under the condition that DCT and 2DPCA algorithms have the approximate dimension reduction effect. At last, the comparative simulation experiment is performed on DCT and 2DPCA algorithms respectively with the AT＆T face database and JAFFE facial expression database.
出处
《河南大学学报（自然科学版）》
CAS
北大核心
2008年第6期636-639,共4页
Journal of Henan University:Natural Science
基金
河南省科委自然科学基金项目(No.0523020600)
河南省高校创新人才工程项目(2005KYCX012)
关键词
DCT
图像压缩
特征降维
人脸识别
人脸表情识别
DCT
image compression
feature dimension reduction
face recognition
facial expression recognition
作者简介
蒋斌（1983-），男，河南新乡人，硕士研究生，主要研究方向是图像处理和模式识别．
