Adaptive shadow removal algorithm for face images
Zhen Zeng, Rumin Zhang, Jianwen Chen, Liaoyuan Zeng, Wenyi Wang, Sean McGrath · 2018
In the real world, illumination is an inevitable factor in face recognition. It has been proved that illumination variations are more significant than inherent variations between persons. This paper proposes an adaptive image processing method, which can not only suppress the effect of light in face recognition, but also remove shadow caused by illumination. In this paper, first, adaptive illumination preprocessing is performed to make the image have appropriate brightness. Then, the shadows boundaries of the image is extracted and binarized to obtain the shadow boundaries mask. Finally, the high-quality face image without shadows is reconstructed based on the mask of shadows boundaries and the face image after the illumination preprocessing. Experiments on the CMU-PIE dataset have shown that our method can achieve both good visual effects and a significant improvement in face recognition accuracy.