Facial expression recognition using Gabor filter and multi-layer artificial neural network

• Published in: 2017 International Conference on Information, Communication, Instrumentation and Control (ICICIC) pp. 1 - 5
• Main Authors: Verma, Kunika, Khunteta, Ajay
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2017
• Subjects: Artificial Neural Network (ANN); Artificial neural networks; Face; Face detection; Face recognition; Facial Expression Recognition (FER); Feature extraction; Gabor Filter; Gabor filters; Viola-Jones algorithm
• DOI: 10.1109/ICOMICON.2017.8279123

This paper deciphers the Facial Expression Recognition (FER) using Gabor Filter and Artificial Neural Network (ANN), extracts the facial expression using Gabor filter and then classify the facial expressions using the multi-layer artificial neural network. Recognizing facial expressions of human beings in an image processing by a computer is an interesting and challenging research work. This paper is based on detection and classification of facial emotion expressions. At first, we design an algorithm to detect the face reason image in the whole image using Viola-Jones detection algorithm, then by using Gabor filter extracts the facial features in the spatial domain. The Gabor filter is used to capture the whole frequency spectrum in all directions. And then extract meaningful facial features using Gabor Filter. Finally, they have been successfully classified the facial expressions using the extracted Gabor features of face image used as an input to the Artificial Neural Network classifier. The experimental results on database images of JAFFE show the robustness and better recognition rates of the proposed approach.