基于模糊线性判别分析的人脸识别算法设计毕业设计（论文）.doc

基于模糊线性判别分析的人脸识别算法设计 学 院 专 业 班 级 学 号 姓 名 指导教师 负责教师 摘 要 关键词；；Face Recognition Algorithm based on Fuzzy linear discriminant analysis Abstract Face recognition technology is a kind of Biological recognition technology. With its immediacy, uniqueness and convenience, etc. It gets more and more widely used in terms of public security, customhouse, traffic, finance, video conference, the study on robot’s intelligence. Face recognition technology is a frontier topic in the field of pattern recognition. In the past few decades, the researchers tried to use a computer to imitate humans ability to recognize faces, and a lot of effective algorithm of face recognition was proposed, and they used different technology increased the average recognition rate of face recognition algorithm. This paper focuses on a face recognition method which combining with the principal component analysis and fuzzy linear discriminant analysis (FLDA) algorithm. This method obtains the characteristics space of the training sample with the principal component analysis(PCA) algorithm, then on the basis of this calculation, get another FLDA’S feature subspace which has lower dimensions. In this FLDA’s feature subspace, samples of the same category are as near as possible, different types of sample are as disperse as possible (In other words, after the dimension reduction, the same person face image are as near as possible, the different human face image are as far as possible). The fuzzy technology is used in fuzzy LDA to optimize feature extraction, it can get a better class center position estimate with using membership information to describe the distribution information of the sample. The experimental results on Yale and ORL face database show that this algorithm has high recognition rate. Keywords: Face Recognition; Principal Component Analysis; Fuzzy Linear Discriminate Analysis; Eigenface 目 录 1 绪 论 1 1.1 人脸识别的研究背景和意义 2 1.2 人脸识别的发展史和应用 3 1.2.1 发展历史及发展现状 3 1.2.2 应用和