摘要
针对经典PCA人脸识别算法受光照条件影响的缺点,本文提出了一种新的改进的PCA人脸识别算法.该算法在图像的预处理阶段,利用图像灰度的线性变换,增大每幅图像的对比度和亮度;对预处理后的图像则利用经典PCA算法进行处理,并在识别阶段,通过对体现光照变化的三个主分量进行加权处理,减少它们在识别中占的比重.实验结果表明,该算法是有效的,能够减少光照条件对人脸识别的影响.
A new optimization method of PCA face recognition is proposed for variable illuminaconditions. In pre-processing stage, the new method increases contrast grade and brightness of each gray image through linear transformation, and the pretreated images are processed according to classical PCA face recognition. In the recognition stage, the first three principal components which reflected the illumination conditions on were given a suitable weight in order to reduce their proportion, The experimental results show that the new method can effectively reduce the illumination effect.
出处
《大连交通大学学报》
CAS
2008年第4期48-51,共4页
Journal of Dalian Jiaotong University
关键词
人脸识别
光照
线性变换
主分量加权
face recognition
illumination
linear transformation
PCA weighted