In order to overcome the shortcomings of Principal Component Analysis (PCA) and bionic methods in feature extracting and dimension reduction, a method for extracting Gabor features of face images based on Gabor wavelet is presented. First, Gabor features are extracted from face images. After reduced by 2DPCA algorithm, the features are reduced further by rough set. Then the nearest classifier is trained for classification. The experiments being performed on Yale Face Database B human face image database show the method presented in this paper is superior to that of bionic recognition algorithm and PCA algorithm. ©2010 IEEE.