计算机工程2011，Vol.37Issue(5)：219-220,223,3.
基于二值数据贝叶斯子空间的人脸识别算法
Face Recognition Algorithm Based on Binary Bayesian Subspace
摘要
Abstract
Traditional face recognition algorithm based on Bayesian space is assumed to meet the Gaussian distribution of the sample space.In fact the sample space is very complicated and does necessarily satisfy the Gaussian distribution.This paper presents a new face recognition algorithm in the Bayesian space.By setting the image gray-level threshold and counting the frequency of the pix and calculate the class conditional probability density, this algorithm gets posterior probability by the Bayesian formula.This method overcomes the shortcomings of traditional Bayesian approach hard to find within-class and between-class covariance matrix, and it is easy to use.Experimental results show that the method is feasible, superior to the traditional algebra-based face recognition algorithms(PCA, LDA and PCA + LDA).关键词
贝叶斯子空间/人脸识别/后验概率Key words
Bayesian subspace/ face recognition/ posterior probability分类
信息技术与安全科学引用本文复制引用
曾岳,冯大政,何新田..基于二值数据贝叶斯子空间的人脸识别算法[J].计算机工程,2011,37(5):219-220,223,3.基金项目
国家自然科学基金资助项目(60372049) （60372049）
江西省科技计划青年基金资助项目(GJJ09412) （GJJ09412）
