摘要
将一个人脸图象矩阵视为一矢量,先通过主元分析的方法构造优化的"人脸空间",并在此基础上引入模糊数学中的矢量隶属函数、隶属度等概念,提出和设计了一种新的基于模糊隶属函数的主元分析人脸特征抽取和识别算法。实验结果表明,这种识别算法既可行又具有良好的识别能力。
In this paper,the face image matrix is viewed as a vector and an optimal 'face space'is constructed based on principal component analysis. On this basis,the concepts of vector membership function and membership degree in fuzzy mathematics are introduced,and a new face feature extraction and recognition algorithm of principal component analysis based on fuzzy membership functions is presented.Experimental results show that the recognition algorithm is feasible and has good recognition capability.
出处
《计算机工程与科学》
CSCD
2004年第6期55-57,共3页
Computer Engineering & Science
基金
国家863计划资助项目(2001AA144170)
