Human Facial Expression Recognition System Using Artificial Neural Network Classification of Gabor Feature Based Facial Expression Information

Facial expressions contribute highly in conveying the feelings of a person. An emotion recognition system through facial expression recognition is proposed in this paper. Preprocessed input images are segmented into four facial expression regions by following the proposed highly effective image segmentation method. 2D Gabor filter with different frequencies and orientations are used to extract features from the segmented parts. Reduction of the dimension of the extracted features is done using downsampling and Principal Component Analysis (PCA). Classification of the features is done using the artificial neural network (multilayer perceptrons with backpropagation). To evaluate the performance of the proposed method three widely used facial expression datasets (JAFFE, CK+, RaFD) are used. Performance on these datasets by the proposed method is compared with the performance on these datasets by other methods to indicate that state-of-the-art performance is achieved by the proposed method.

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