A NOVEL LBP-BASED COLOR DESCRIPTOR FOR FACE RECOGNITION

LBP-based color features have shown excellent performance for color face recognition tasks, such as Color LBP, CLBP and LCVBP. However, existing methods encode the inter-channel information on pairs of color channels by applying the same spatial structure as that used in the intra-channel encoding. This results in a very high dimensional feature vector yet in-effective in encoding inter-channel information. Moreover, the difference of pixel values across color channels may not be a proper measure if they are not quantitatively comparable. To tackle these problems of existing methods, we propose a novel LBP-based color feature, Ternary-Color LBP (TCLBP), to encode the inter-channel information more effectively and efficiently. Extensive experiments on 4 public face databases, Color FERET, Georgia Tech, FRGC and LFW, are conducted to verify the effectiveness of the proposed TCLBP color feature for face recognition. Results show that the proposed TCLBP leads to visibly better face recognition performance than Color LBP, CLBP and LCVBP consistently over the 4 databases.