FACE SKETCH RECOGNITION BY LOCAL RADON BINARY PATTERN: LRBP

In this paper, we propose a new face descriptor to directly match face photos and sketches of different modalities, called Local Radon Binary Pattern (LRBP). LRBP is inspired by the fact that the shape of a face photo and its corresponding sketch is similar, even when the sketch is exaggerated by an artist. Therefore, the shape of face can be exploited to compute features which are robust against modality differences between face photo and sketch. In LRBP framework, the characteristics of face shape are captured by transforming face image into Radon space. Then, micro-information of face shape in new space is encoded by Local Binary Pattern (LBP). Finally, LRBP is computed by concatenating histograms of local LBPs. In order to capture both local and global characteristics of face shape, LRBP is extracted in a spatial pyramid fashion. Experiments on CUFS and CUFSF datasets indicate the efficiency of LRBP for face sketch recognition.