Facial Expression Recognition Based on Local Double Binary Mapped Pattern

Abstract

Local feature descriptors play an important role in facial expression recognition. Local Binary Pattern (LBP) only considers the signal information of the difference between the gray value of the center pixel and the neighbor pixel. It does not take the magnitude information into consideration and has poor robustness. Local Mapped Pattern (LMP) is not ideal for discriminating differences between different textures and experimental result is not excellent. This paper proposes a novel feature descriptor based on gray-level difference mapping, called Local Double Binary Mapped Pattern (LDBMP).This new approach is an improvement over the previous LBP and LMP, not only retains the advantages of LBP and LMP but also preserves the information of magnitude and captures nuances that occur in the image. In our experiments, the new descriptor performs favorably.