Abstract: In order to solve the face detection problem with complex lighting conditions, this paper presents a new method for face illumination compensation. The high-pass filtering is used to enhance edge information, the logarithmic transformation and the exponential transformtion are used to adjust the global brightness simultaneously, Nonlinear variances are applied to reduce the impact of the local highlights and shadows. The uneven lighting problem is lighten. Comparison experiments are conducted on the Yale B face dataset, Orl face dataset and our own face dataset. The results demonstrate that the illumination compensation method can significantly improve face detection rate.

Key words: Adaboost method, face detection, illumination compensation, histogram, Retinex

摘要： 为了解决复杂光照条件下的人脸检测问题，提出一种人脸光照补偿新方法。该方法先使用高通滤波增强边缘信息，同时利用对数变换和指数变换调节全局亮度，最后利用非线性变化削弱局部高光和阴影的影响，改善图像光照不均衡的情况，最终实现光照补偿。在YaleB人脸库、Orl人脸库以及自建人脸库上分别对光照不均匀人脸图像和均匀光照下的人脸图像进行了实验，证明该方法能有效地进行光照补偿，提高人脸检测率。

关键词: Adaboost算法, 人脸检测, 光照补偿, 直方图, Retinex