Robust Face Recognition Based on Texture Analysis

In this paper, we present a new framework for face recognition with varying illumination based on DCT total variation minimization (DTV), a Gabor filter, a sub-micro-pattern analysis (SMP) and discriminated accumulative feature transform (DAFT). We first suppress the illumination effect by using the DCT with the help 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 using DAFT. Our system is verified with experiments on the AR and the Yale face database B.