Improved Facial Expression Recognition Based on DWT Feature for Deep CNN

Ridha Bendjillali, Mohammed Beladgham, Khaled Merit, Abdelmalik Taleb-Ahmed
2019 Electronics  
Facial expression recognition (FER) has become one of the most important fields of research in pattern recognition. In this paper, we propose a method for the identification of facial expressions of people through their emotions. Being robust against illumination changes, this method combines four steps: Viola–Jones face detection algorithm, facial image enhancement using contrast limited adaptive histogram equalization (CLAHE) algorithm, the discrete wavelet transform (DWT), and deep
more » ... nal neural network (CNN). We have used Viola–Jones to locate the face and facial parts; the facial image is enhanced using CLAHE; then facial features extraction is done using DWT; and finally, the extracted features are used directly to train the CNN network, for the purpose of classifying the facial expressions. Our experimental work was performed on the CK+ database and JAFFE face database. The results obtained using this network were 96.46% and 98.43%, respectively.
doi:10.3390/electronics8030324 fatcat:dnjji46sazgxlnomhbgsvi2h6q