Facial Expression Recognition System Using Local Texture Features of Contourlet Transformation

Australian Journal of Basic and Applied Sciences, 10(2), January 2016

4 Pages Posted: 10 Jul 2017

See all articles by R. Suresh

R. Suresh

PRIST University, Department of Computer Science and Engineering, Students

S. Audithan

PRIST University - Department of Computer Science and Engineering

G. Kannan

PRIST University, Department of Computer Science and Engineering, Students

K. Raja

Bharathidasan University, Students

Date Written: January 8, 2016

Abstract

Facial expression is important in interpersonal relations also significant among communication in both human and machine iteration. Thus the importance of facial expression recognition is becoming active research area in last three decades. In this study, a robust and automated facial expression recognition system is proposed using facial images. It is implemented based on Contourlet transform, Discriminative Robust Local Binary Pattern (DRLTP) and K-Nearest Neighbour (KNN) classifier. To extract facial features, the given facial image is decomposed using Contourlet Transform. Then, DRLTP features are computed from each decomposed contourlet coefficients. Finally, KNN classifier is used for the classification of facial expressions. Experiments are carried out using benchmark Japanese Female Facial Expression (JAFFE) database. The proposed system achieves satisfactory classification accuracy over 75%.

Keywords: Facial Expression Recognition, Contourlet Transform, K-Nearest Neighbor Classifier, Discriminative Robust Local Binary Pattern.

Suggested Citation

Suresh, R. and Audithan, S. and Kannan, G. and Raja, K., Facial Expression Recognition System Using Local Texture Features of Contourlet Transformation (January 8, 2016). Australian Journal of Basic and Applied Sciences, 10(2), January 2016. Available at SSRN: https://ssrn.com/abstract=2791840

R. Suresh (Contact Author)

PRIST University, Department of Computer Science and Engineering, Students ( email )

Thanjavur
India

S. Audithan

PRIST University - Department of Computer Science and Engineering

Thanjavur, Tamil Nadu 613403
India

G. Kannan

PRIST University, Department of Computer Science and Engineering, Students

Thanjavur
India

K. Raja

Bharathidasan University, Students

Tiruchirappalli
India

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