频域光照归一化的人脸识别

Face Recognition Based on Illumination Normalization in Frequency-Domain

为了降低人脸识别对环境条件的要求,克服光照对人脸识别的影响,通过分析人脸图像的幅频特性和相频特性,提出了频域光照归一化的人脸识别,对任何光照条件下采集的图像经过归一化后,光照与训练库中完全相同,同时保留了人脸的可区分性。人脸之间差异的信息量一般较少,运用最小非零特征向量作为人脸特征。实验仿真表明,与传统方法相比,频域光照归一化人脸识别方法对光照变化具有鲁棒性。

In order, to reduce the impact environmental requirements and overcome the effects of illumination on face recognition, a novel recognition method is presented based on normalization illumination in frequency-domain, via analyzing the Amplitude-frequency and phase-frequency characteristics of human faces. Collected images under any light conditions are normalized so that the light is exactly the same for the training images, while retaining the distinctive features of human faces. As the different information of faces is usually small, the smallest non-zero eigenvector is chosen as a facial feature. Experimental results show that our method is more robust against light than traditional methods.