Facial expression recognition algorithm using LGC based on horizontal and diagonal prior principle

Abstract

The traditional Local Binary Pattern (LBP) algorithm can analyze the center pixel and neighboring pixels of the gray relationship, using in facial expression recognition, but you cannot consider the eyes, mouth, forehead and other areas in the expression feature different trends in the gradient direction. Firstly, we propose the Local Gradient Coding (LGC) algorithm, though the binary encoding to the horizontal, vertical and diagonal gradients respectively, to produce the fusion characteristic, then this can fully describe the facial muscles texture, wrinkles and other local deformation of contains the expression information. On the other hand, in order to reduce the computational complexity, and to remove the redundant, while not lose the main information contained in the face texture expression. This paper proposes and optimizes a new LGC operator based on horizontal and diagonal gradient prior principle (LGC-HD). The experimental results from JAFFE database show that, LGC-HD algorithm is more quickly and effectively to extract facial expression feature than LGC algorithm. Comparing to the traditional LBP algorithm, LBP uniform pattern and Gabor filtering, this LGC-HD algorithm has a significant advantage in the recognition accuracy and run time.