| Abstract: | In order to improve the recognition rate of face recognition algorithm, a new algorithm of face recognition is proposed based on Gabor wavelet transform and Supervised Locally Linear Embedding (SLLE). Gabor wavelet is introduced as a method to extract Gabor magnitude features by convolving the normalized face image with multi scale and multi orientation Gabor filters. In the feature extraction module, the dimension of Gabor features is reduced by SLLE. A minimum distance classifier is trained for classification. With the test of the ORL and YALE face database, it is found that 3.5 %~37.8% increase in recognition rate can be achieved compared with other algorithms. |
