不同光照条件下特征脸方法的改进研究

Eigenface Optimization Research for Variable Illumination Conditions

提出了一种针对人脸图像的预处理方法,针对光照条件影响对特征主分量进行了改进研究。首先介绍了特征脸识别方法的起源与实现,然后介绍了添加对自身图像灰度值零均值的预处理方法。基于FERET人脸图像组建特征库和测试库,对特征脸方法中的前三个主分量进行具体分析,得出了其对光照敏感的规律,及在光照影响较为严重的情况下主分量的最佳选取方法。

A pre-processing method for face images is introduced firstly and the principal components of the eigenfaces are researched for variable illumination conditions. The source and the realization of the eigenface method are introduced and the pre-processing step of the zero mean of every face image is added. Based on the feature database and the probe database from FERET face images, the first three principal components are analysed and the rules of their influences by variable illumination conditions are concluded. The optimal method of choosing principal components is presented when influenced by illumination conditions severely.