Feature extraction is one of the key steps in face recognition. In this paper, common vector is used to extract features from null space of within-class scatter matrix, which is independent of the sample index in the same class and accelerates the speed of feature extraction. Furthermore, effective features in regular space are extracted to enhance the performance of face recognition. The proposed method not only solves the small sample size problem, but also extracts more effective features from face images. Experimental results on two popular databases demonstrate the effectiveness of the proposed method.