A Hybrid Method of Feature Extraction for Facial Expression Recognition

Facial Expression Recognition is necessary for designing any human-machine interface. The main issue of Facial Expression Recognition is to decide what features are required to represent a Facial Expression. In this paper, we propose the hybrid technique for facial expression recognition. In this paper we proposed a combined method of feature extraction using Discrete Cosine Transform, Gabor Filter, Wavelet Transform and Gaussian distribution to improve the recognition rate. Experimental are performed on seven expressions, (anger,disgust, fear, happiness, sadness, surprise, neutral ) of JAFFE dataset. The result of Proposed work is compared with result of individual Feature Extraction Techniques that show that Facial Expression Recognition Rate can be improved by combining best features of DCT, Gabor Filter, Wavelet Transform and Gaussian Distribution.