Face recognition based on the combination of histogram features and rough location information of facial parts

In this paper, an improved face recognition algorithm based on adjacent pixel intensity difference quantization (APIDQ) histogram method is proposed. By utilizing the rough location information of the facial parts, the facial area is divided into 5 individual parts, and then APIDQ is applied on each facial component. Recognition results are firstly obtained from different parts separately and then combined by weighted averaging. The experimental result shows that top 1 recognition rate of 97.6% is achieved when evaluated by FB task of the FERET database.