本文提出了一種基于小波和DFB-PCA 的人臉識(shí)別算法。將識(shí)別圖像先用小波變換對(duì)其分解后，再對(duì)低頻子帶進(jìn)行DFB-PCA 識(shí)別。實(shí)驗(yàn)結(jié)果表明，該方法有利于減少光照、姿勢(shì)和表情等因素的影響，降低噪聲和圖像識(shí)別的維數(shù)，且具有較好的魯棒性。與直接在原圖像上采用PCA 識(shí)別相比，可提高對(duì)圖像的計(jì)算速度和識(shí)別效率。
關(guān)鍵詞：小波變換；DFB-PCA；圖像識(shí)別；人臉識(shí)別

Face Recognition Algorithm Researching Based on Wavelet and DFB-PCA Zhang Jian-ge, Wang Shi-qing, Sheng Guang-lei (College of Information Engineer, Zhengzhou University, Zhengzhou 450002, China) Abstract: In this paper, face recognition algorithm based on wavelet and DFB-PCA which first decomposes recognition images using wavelet transformation and then recognizes the low frequency subband using DFB-PCA algorithm has been proposed. Experimental results demonstrate that the proposed algorithm is propitious to reduce the influence of illumination , pose, expression and so on, reduce the noise of images and the dimension of recognition images, and has a robust performance. The proposed algorithm can improve computing speed of images and the recognition rate compare with the algorithm which uses PCA only on original images.
Key words: wavelet transformation; DFB-PCA; image recognition; face recognition