Facial expression recognition based on DWT feature for deep CNN

Bendjillali Ridha Ilyas; Beladgham Mohammed; Merit Khaled; Abdelmalik Taleb Ahmed; Alouani Ihsen

doi:10.1109/CoDIT.2019.8820410

Facial expression recognition based on DWT feature for deep CNN

Bendjillali Ridha Ilyas, Beladgham Mohammed, Merit Khaled, Abdelmalik Taleb Ahmed, Alouani Ihsen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

29 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Proceedings of the 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	5
ISBN (Electronic)	9781728105215
ISBN (Print)	9781728105222
DOIs	https://doi.org/10.1109/CoDIT.2019.8820410
Publication status	Published - 02 Sept 2019
Externally published	Yes
Event	6th International Conference on Control, Decision and Information Technologies - Paris, France Duration: 23 Apr 2019 → 26 Apr 2019 https://doi.org/10.1109/CoDIT46672.2019

Publication series

Name	International Conference on Control, Decision and Information Technologies: Proceedings
ISSN (Print)	2576-3547
ISSN (Electronic)	2576-3555

Conference

Conference	6th International Conference on Control, Decision and Information Technologies
Abbreviated title	CoDIT
Country/Territory	France
City	Paris
Period	23/04/2019 → 26/04/2019
Internet address	https://doi.org/10.1109/CoDIT46672.2019

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10.1109/CoDIT.2019.8820410Licence: Unspecified

Cite this

Ilyas, B. R., Mohammed, B., Khaled, M., Ahmed, A. T., & Ihsen, A. (2019). Facial expression recognition based on DWT feature for deep CNN. In Proceedings of the 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019 (International Conference on Control, Decision and Information Technologies: Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CoDIT.2019.8820410

Ilyas, Bendjillali Ridha ; Mohammed, Beladgham ; Khaled, Merit et al. / Facial expression recognition based on DWT feature for deep CNN. Proceedings of the 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (International Conference on Control, Decision and Information Technologies: Proceedings).

@inproceedings{e690ea26f2c94104891c37f609ce25b6,

title = "Facial expression recognition based on DWT feature for deep CNN",

abstract = "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.",

author = "Ilyas, {Bendjillali Ridha} and Beladgham Mohammed and Merit Khaled and Ahmed, {Abdelmalik Taleb} and Alouani Ihsen",

year = "2019",

month = sep,

day = "2",

doi = "10.1109/CoDIT.2019.8820410",

language = "English",

isbn = "9781728105222",

series = "International Conference on Control, Decision and Information Technologies: Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "Proceedings of the 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019",

address = "United States",

note = "6th International Conference on Control, Decision and Information Technologies, CoDIT ; Conference date: 23-04-2019 Through 26-04-2019",

url = "https://doi.org/10.1109/CoDIT46672.2019",

}

Ilyas, BR, Mohammed, B, Khaled, M, Ahmed, AT & Ihsen, A 2019, Facial expression recognition based on DWT feature for deep CNN. in Proceedings of the 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019. International Conference on Control, Decision and Information Technologies: Proceedings, Institute of Electrical and Electronics Engineers Inc., 6th International Conference on Control, Decision and Information Technologies, Paris, France, 23/04/2019. https://doi.org/10.1109/CoDIT.2019.8820410

Facial expression recognition based on DWT feature for deep CNN. / Ilyas, Bendjillali Ridha; Mohammed, Beladgham; Khaled, Merit et al.
Proceedings of the 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (International Conference on Control, Decision and Information Technologies: Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Facial expression recognition based on DWT feature for deep CNN

AU - Ilyas, Bendjillali Ridha

AU - Mohammed, Beladgham

AU - Khaled, Merit

AU - Ahmed, Abdelmalik Taleb

AU - Ihsen, Alouani

PY - 2019/9/2

Y1 - 2019/9/2

N2 - 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.

AB - 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.

U2 - 10.1109/CoDIT.2019.8820410

DO - 10.1109/CoDIT.2019.8820410

M3 - Conference contribution

SN - 9781728105222

T3 - International Conference on Control, Decision and Information Technologies: Proceedings

BT - Proceedings of the 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 6th International Conference on Control, Decision and Information Technologies

Y2 - 23 April 2019 through 26 April 2019

ER -

Ilyas BR, Mohammed B, Khaled M, Ahmed AT, Ihsen A. Facial expression recognition based on DWT feature for deep CNN. In Proceedings of the 6th International Conference on Control, Decision and Information Technologies, CoDIT 2019. Institute of Electrical and Electronics Engineers Inc. 2019. (International Conference on Control, Decision and Information Technologies: Proceedings). doi: 10.1109/CoDIT.2019.8820410

Facial expression recognition based on DWT feature for deep CNN

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