Abstract—Facial expression analysis plays a significant role for human computer interaction. Automatic analysis of human facial expression is still a challenging problem with many applications. In this paper, we propose neuro-fuzzy based automatic facial expression recognition system to recognize the human facial expressions like happy, fear, sad, angry, disgust and surprise. Initially facial image is segmented into three regions from which the uniform Local Binary Pattern (LBP) texture features distributions are extracted and represented as a histogram descriptor. The facial expressions are recognized using Multiple Adaptive Neuro Fuzzy Inference System (MANFIS). The proposed system designed and tested with JAFFE face database. The proposed model reports 95.29% of classification accuracy.
Index Terms—Adaptive neuro-fuzzy inference system, Facial expression, Local binary pattern, Uniform LBP Histogram.
V. Gomathi, is with the National Engineering College, Kovilpatti, Tamil Nadu, INDIA (Mobile: 99948 46309; e-mail: vgcse@ nec.edu.in).
Dr. K.Ramar, is with the National Engineering College, Kovilpatti, Tamil Nadu, INDIA (Mobile: 94426 24114; e-mail: drkrcse@ nec.edu.in).
A. Santhiyaku Jeevakumar, was with the National Engineering College, Kovilpatti, Tamil Nadu, India
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Cite: V. Gomathi, K. Ramar and A. Santhiyaku Jeevakumar, "A Neuro Fuzzy approach for Facial Expression Recognition using LBP Histograms,"
International Journal of Computer Theory and Engineering vol. 2, no. 2, pp. 245-249, 2010.
