摘要
针对选定PCA特征空间维数的问题,提出了一种混沌遗传算法和主成分分析相融合的人脸识别方法。利用混沌遗传算法对PCA变换后的特征向量进行选择,快速搜索到了有利于分类的特征子空间;在ORL人脸库上的实验表明,该方法不但降低了特征空间的维数,提高了识别速度,而且获得了比采用其他方法更好的识别性能。
Aiming at the problem of how to determine the dimension of the eigenvectors in principal component analysis（PCA）,a novel face recognition method based on the combination of PCA and chaos genetic algorithm（CGA） is proposed.Then CGA is used in feature（eigenvector） selection after the transformation of PCA,which can quickly find out feature subspace that is beneficial to classification.The experiment results based on ORL indicate that the proposed method not only reduces the dimensions of face feature space with highly accurate recognition rate,but also achieves higher recognition performance than other methods.
出处
《青海大学学报（自然科学版）》
2010年第5期30-33,共4页
Journal of Qinghai University(Natural Science)
关键词
人脸识别
主成分分析
混沌遗传算法
face recognition
principal component analysis
chaos genetic algorithm
