基于Gabor小波和LDA的人脸识别算法研究

摘要

为了克服光照、表情变化等因素对人脸识别的影响,提出了一种基于Gabor小波和LDA的人脸识别方法,该方法充分利用了Gabor小波的空间局部性和万向选择性,先提取原始人脸图像的Gabor特征,然后对其作LDA变换得到最佳分类特征.依据ORL和YALE人脸库进行实验,实验结果表明,该识别方法对各种变化具有一定稳健性,最高识别率可达到99％.%To overcome the negative effect of factors such as illumination and expression on face recognition ,a method of Gabor wavelet and Linear Discriminant Analysis( LDA) for face recognition is proposed. This method makes full use of the desirable characteristics of spatial locality and orientation selectivity of Gabor filters. At first,Gabor features are extracted on the original intensity images,then the best classification feature is acquired by utilizing the LDA. Experimental results on ORL and YALE database indicate that this method is robust to large illumination and the sampling vectors numbers,and the best recognition rate can achieves 99%.