This paper proposes two effective color local texture features, i.e., color local Gabor wavelets (CLGWs) and color local binary pattern (CLBP), for face recognition (FR).This method encodes the discriminative features by combining both color and texture information as well as its fusion approach. To make full use of both color and texture information, the opponent color texture features are used. The opponent features capture the spatial correlation between spectral bands and taken into the generation of CLGW and CLBP. In addition, to combine multiple color local texture features, a feature-level fusion framework used. This method is able to provide excellent recognition rates and significant improvement in the FR accuracy when recognizing face images taken under a severe change in illumination as well as for low- resolution face image. Also, this method improves FR performance and feasible in comparison with other state-of-the-art color FR methods.