This paper proposes a face recognition algorithm based on wavelet and DFB-PCA. The recognition image is first decomposed by wavelet transform, and then DFB-PCA recognition is performed on the low-frequency subband. Experimental results show that this method is beneficial to reduce the influence of factors such as lighting, posture and expression, reduce noise and the dimension of image recognition, and has good robustness. Compared with directly using PCA recognition on the original image, it can improve the calculation speed and recognition efficiency of the image. Keywords: wavelet transformation; DFB-PCA; image recognition; face recognition 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
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