基于MCD稳健估计的PCA人脸识别算法
张蓓;王顺芳
【期刊名称】《计算机工程与设计》 【年(卷),期】2015(000)003
【摘要】To solve the problems in facial recognition that recognition rates are often affected by face modification ,partial occlu‐sion ,noise and other uncertain factors ,a MCDPCA algorithm was proposed to improve the face recognition effect .The eigenfa‐ces was extracted using the principal component analysis (PCA) method ,the minimum covariance determinant (MCD) method was combined for detecting the outliers and removing noise .Specifically ,MCD algorithm was used to obtain a robust covariance matrix estimate for face images ,then PCA was used on the basis of this covariance matrix estimate to extract important facial features for recognition .Experimental results demonstrate that for face recognition with occlusion or noise ,the proposed MCDP‐CA method performs much better than traditional PCA as far as the recognition rates are concerned .%针对人脸识别中，识别效果易受人脸修饰、部分遮挡、噪声干扰等不确定因素影响的问题，提出一种MCDPCA人脸识别算法以改进识别效果。基于主成分分析（PCA）进行特征脸提取，结合最小协方差行列式方法（MCD）进行异常点检测和抗噪。针对人脸图像使用MCD算法，求出稳健的协方差矩阵估计，基于此协方差估计矩阵使用PCA技术提取重要的人脸特征用于识别。实验结果表明，在有遮挡和噪声
基于MCD稳健估计的PCA人脸识别算法
