视频中适应光照可变情况下的人脸识别方法

提出一种结合使用自适应直方图均衡(AHE)、Gabor滤波器及局部三值模式(LTP)描述器进行视频中上下左右和正面光照条件下识别人脸的方法。首先，使用AHE对来自YaleB与CMU-PIE数据库的人脸图片进行降噪处理。然后用Gabor滤波器进行卷积，提取出相应的Gabor特征图，针对每一个Gabor特征图利用LTP描述器提取出局部邻域关系模式。最后由这些模式的区域直方图形成的序列来描述人脸。YaleB人脸库以及CMUPIE人脸库验证该方法的有效性。

Adaptive Method for Video-Based Face Recognition under Variable Illumination

A method is proposed, which combines adaptive histogram equalization (AHE), Gabor wavelet and LTP, to improve the video-based facial recognition under left, right, up, down and front illumination. Firstly, the AHE is used to reduce illumination variations on the existed face images from YaleB and CMU PIE face databases. Then, the images are convolved with Gabor filters to extract their corresponding Gabor feature maps and the LTP is used on each Gabor feature map to extract the local neighbor pattern. Finally, the input face image is described by using the histogram sequence extracted from all these region patterns. The results compared with the published results on YaleB and CMU PIE face databases of changing illumination verified the validity of the proposed method.