Facial Expression Recognition using Local Gabor Binary Pattern(LGBP) and Principle Component Analysis (PCA)

Facial Expression Recognition is one of the active research area in the field of Human Machine Interaction (HMI) because of its several applications such as human emotion analysis, stress level and lie detection. In this paper, an algorithm for facial expression recognition has been proposed which integrate the Local Binary Patterns (LBP), Gabor filter and Principal Component Analysis (PCA). The proposed technique has been applied on JAFFE database. The comparative analysis on the basis of average recognition rate has been performed for each individual and integrated approach. The results shows highest recognition rate while combining LGBP and PCA, which is 87.5. The results indicate that when we integrate LBP, Gabor filter and PCA, then it provides high recognition rate. Keywords—Facial expression analysis (FER), Principal Component Analysis (PCA), Local Gabor Binary Patterns (LGBP), Gabor filter. (key words)