A Novel Face Recognition Algorithm for Distinguishing Faces with Various Angles

作     者：Yong-Zhong Lu 

作者机构：School of Software Engineering Huazhong University of Science and Technology Wuhan 430074 PRC 

出 版 物：《International Journal of Automation and computing》 (国际自动化与计算杂志（英文版）)

年 卷 期：2008年第5卷第2期

页      面：193-197页

核心收录：

学科分类：08[工学] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work was supported by Natural Science Foundation of Huazhong University of Science and Technology of PRC(No.2007Q006B) 

主　　题：Face recognition approximate dynamic programming (ADP) particle swarm optimization (PSO) 

摘      要：In order to distinguish faces of various angles during face recognition, an algorithm of the combination of approximate dynamic programming （ADP） called action dependent heuristic dynamic programming （ADHDP） and particle swarm optimization （PSO） is presented. ADP is used for dynamically changing the values of the PSO parameters. During the process of face recognition, the discrete cosine transformation （DCT） is first introduced to reduce negative effects. Then, Karhunen-Loeve （K-L） transformation can be used to compress images and decrease data dimensions. According to principal component analysis （PCA）, the main parts of vectors are extracted for data representation. Finally, radial basis function （RBF） neural network is trained to recognize various faces. The training of RBF neural network is exploited by ADP-PSO. In terms of ORL Face Database, the experimental result gives a clear view of its accurate efficiency.