Intelligent System Based on Wavelets for Automatic Facial Emotion Recognition

Fiorella Andrea Alejos Yarasca, Santiago Domingo Moquillaza Henriquez

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Resumen

Facial emotion recognition is very important for social communication. Whereby through the years it has done many studies and researches about automatic emotion recognition. Generally, the facial emotion recognition systems are composed of the pre-processing phase, the features extraction phase and the classification phase. This article proposes a method for automatic facial emotion recognition in digital images. This method uses histogram equalization to improve special lighting conditions during the pre-processing of images, two-dimensional discrete wavelet transform and PCA algorithms are used to extract and reduce features. Finally it uses a support vector machine linear to predict emotions. The experiments were made using the JAFFE database and CK+. The method achieves more than 93% for average accuracy and it recognizes better the following emotions: Happiness, neutral and surprise. For comparisons, two kinds of classifiers were adopted: Support vector machine and Convolutional Neural Network. Using this last classifier we achieve more than 98% for average accuracy.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728183671
DOI
EstadoPublicada - 21 oct. 2020
Evento2020 IEEE Engineering International Research Conference, EIRCON 2020 - Lima, Perú
Duración: 21 oct. 202023 oct. 2020

Serie de la publicación

NombreProceedings of the 2020 IEEE Engineering International Research Conference, EIRCON 2020

Conferencia

Conferencia2020 IEEE Engineering International Research Conference, EIRCON 2020
País/TerritorioPerú
CiudadLima
Período21/10/2023/10/20

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Publisher Copyright:
© 2020 IEEE.

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