Local and holistic texture analysis approach for face recognition

In this paper, we present a new framework for face recognition under varying illumination based on DCT total variation minimization (DTV), gabor filter, a sub-micro pattern analysis (SMP) and discriminant accumulative feature transform (DAFT). We first suppress the illumination effect by using the DCT with the helps of TV as a tool for face normalization. The DTV image is then emphasized by the gabor filter. The facial features are encoded by our proposed method, the SMP. The SMP image is then transformed to the 2D histogram by using DAFT. Our system is verified with experiments on the AR and the Yale face database B.