Dimensionality reduced local directional number pattern for face recognition

Face recognition and facial expression recognition using local patterns is the order of the day. Local directional number pattern (LDNP) is one of the prominent descriptor for face recognition. LDNP assigns a 3 bit code for each pixel in the image. The resultant LDNP labeled image is divided into regions to form histogram based descriptor. The histogram bins of all the regions are concatenated to form the final descriptor. In contrast to LDNP, a dimensionality reduced local directional number pattern (DR-LDNP) is proposed in this paper. The proposed descriptor computes single code for each block. This is done by X-ORing of the LDNP codes obtained in a single block. During the process, restructuring of the patterns is done by slightly modifying the LDNP coding pattern constraints. The resultant DR-LDNP descriptor outperforms the existing methods. The experimentation is carried out on standard databases like FERET, YALE, ORL, Cohn-Kannade and JAFFEE and obtained good recognition rates compared to other methods.