Facial Expression Recognition Based on DWT Feature for Deep CNN

被引：0
|
作者：
Ilyas, Bendjillali Ridha [1 ]
Mohammed, Beladgham [1 ]
Khaled, Merit [1 ]
Ahmed, Abdelmalik Taleb [2 ]
Alouani, Ihsen [2 ]
机构：
[1] Tahri Mohammed Univ, Dept Elect Engn, Lab TIT, Bechar, Algeria
[2] Univ Valenciennes, CNRS, UMR 8520, Lab IEMN DOAE, Valenciennes, France
来源：
2019 6TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT 2019) | 2019年
关键词：
Facial Expression Recognition (FER); Deep Convolutional Neural Network (deep CNN); Discrete Wavelet Transform (DWT); Histogram Equalization (HE); FACE RECOGNITION; EIGENFACES;
D O I：
10.1109/codit.2019.8820410
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Facial expressions recognition have become one of the most important fields of research in pattern recognition, in this paper, we propose a method to identify the facial expressions of the people through their emotions, this method combining Viola-Jones face detection algorithm, Facial image enhancement using histogram equalization, discrete wavelet transform (DWT) and deep convolution neural network. Extraction results of facial features using DWT are the input of CNN, which are used directly to train the CNN network. Our experimental were performed on CK+ database and JAFFE face database, the obtained results based on this network is 96.46 % and 98.43% respectively.
引用
收藏
页码：344 / 348
页数：5
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