【摘要】 采用基于遗传算法(GA)的二维主成分分析法(2DPCA)进行人脸识别。2DPCA直接以二维图像矩阵为研究对象,以其协方差矩阵的特征向量为投影轴进行特征提取。为了达到识别时的信息最优,将遗传算法融入2DPCA,对协方差矩阵的特征向量进行优化选择得到最优投影轴,并在此基础上提取特征。最后在MIT人脸数据库上进行实验,表明识别率和速度均高于单纯使用2DPCA的方法。更多还原

【Abstract】 A method for automatic face recognition using genetic-algorithm based 2DPCA is proposed.Using a group of eigenvectors of the image matrix’s covariance matrix as its projection axis,2DPCA withdraws features directly regarding two-dimensional image matrix as its study object.In order to get an optimal solution,GA is applied to select projection axis from the eigenvectors of the covariance matrix.Finally,some face recognition experiments using MIT face database are given,which showed the performance of the new method is better than that of 2DPCA.更多还原