Facial expression recognition based on multi-scale centralized binary pattern
Wei Wei · Control theory & applications · 2009
The existing local binary pattern(LBP)operators have disadvantages of long histograms produced by them, low discrimination and high sensitivities to noise.To deal with these problems,we propose the centralized binary pattern(CBP)operator.The CBP operator has several advantages:1)It significantly reduces the histogram dimensionality by comparing pairs of neighbors in the neighborhood;2)It enhances the discrimination by emphasizing the effect of the center pixel point through giving it the largest weight;3)It decreases the white noise influence on face images by modifying the sign function of the existing LBP operator.Moreover,the multi-scale CBP(MCBP)histogram is used as face representation to increase the recognition accuracy.Furthermore,in order to improve the robustness to small deformation of expressional images,the image Euclidean distance(IMED)is introduced and embedded in MCBP.Experiments on JAFFE and Cohn-Kanade facial expression databases demonstrate that the proposed method outperforms other modern approaches and show that IMED can enhance the performance of MCBP in facial expression recognition.