基于几何模型的单幅人脸图像光照补偿方法

为减少光照对人脸识别的影响，本文提出了一种以补偿角度和（Sum of Compensated Angle）为不变量的光照补偿新方法. 首先，补偿角度和是临界补偿状态下两幅图像的光照角度之和. 对某单光源系统，该不变量仅由光照系统决定且为定值. 其次，根据人类头骨在法兰克福截面的形状特性，我们提出了包含人头骨结构的几何人脸光照模型. 据此模型，补偿角度由不变量和待补偿图像的光照角度计算得出，从而将光照补偿转化为简单加法操作. 最后，在Yale B人脸数据库上的补偿结果表明了算法的有效性. 较Sang-Ⅱ Choi的方法显著地提高了大角度下的补偿效果，且在水平和竖直方向上更加鲁棒.

Illumination Compensation for Face Recognition Using Only One Image

To reduce the negative impact of illumination on face recognition, we propose a new illumination compensation method based on image invariant calculation. This invariant (the sum of compensating angles, SCA) is calculated by summing two lighting angles in the proper-compensated state. The SCA only depends on single light source and can be computed only once for a lighting system. Based on the Frankfurt horizontal plane of a human skull, we propose a geometric face model of human skull structure. According to our face model, the compensating angle is calculated from the SCA for a face image taken in the same lighting system. With this compensating angle, the illumination compensation for a face image is done by an additive operation. The experimental results validate our method on the Yale B face database. Compared with Choi0s methods, our method makes obvious improvement on images with large lighting angle, and is more robust to light change in both horizontal and vertical directions.