首页 | 本学科首页   官方微博 | 高级检索  
     

基于独立分量分析和径向基网络的人脸识别方法
引用本文:江帆,高涛,刘金安,陆丽娜. 基于独立分量分析和径向基网络的人脸识别方法[J]. 国外电子元器件, 2008, 16(10)
作者姓名:江帆  高涛  刘金安  陆丽娜
作者单位:西安交通大学,城市学院,陕西,西安,710021
摘    要:人脸识别是当前人工智能和模式识别的研究热点.基于小波分解和定点独立分量分析,提出了一种新的准正面人脸径向基网络识别算法.二维的小波分解具有对表情变化不敏感的特点,可以很好地压缩和表征人脸图像的特征.定点独立分量分析是一种基于高阶统计信息提取特征的方法,克服了一般ICA收敛慢的缺点;径向基网络作为分类器具有很高的推广性能,有利于大容量样本的分类.在对人脸库ORL和YEL的识别实验中,该算法的识别率达到98%以上,与传统算法相比,识别速度和识别率都明显提高.

关 键 词:网络  识别  人工智能/小波变换  人脸识别  径向基网络

Face recognition based on independent component analysis and RBF network
JIANG Fan,GAO Tao,LIU Jin-an,LU Li-na. Face recognition based on independent component analysis and RBF network[J]. International Electronic Elements, 2008, 16(10)
Authors:JIANG Fan  GAO Tao  LIU Jin-an  LU Li-na
Affiliation:JIANG Fan,GAO Tao,LIU Jin-an,LU Li-na(City College Xi'an Jiaotong University,Xi'an 710021,China)
Abstract:Face recognition is an active research area in the artificial intelligence.A new face recognition algorithm using the RBF network is proposed based on wavelet analysis and fixed point ICA.Since wavelet analysis is insensitive to changes in expression,it can effectively express the principal features of the face image by compressing data and corresponding wavelet coefficients.The eigenface of face image can be obtained by the fixed point ICA which is faster than the standard ICA.The RBF network with high gen...
Keywords:network  recognition  artificial intelligence/wavelet transform  face recognition  RBF network  
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号