Facial Expression Recognition Based on Texture Features

Authors

  • Alaa Nabeel Haj Najeb Software and Information Systems Dept., Tishreen University, Latakia, Syria
  • Nasser Nasser

DOI:

https://doi.org/10.29194/NJES.24020144

Keywords:

Expression Recognition, Feature Extraction, Texture, LBP Variants, Image Processing

Abstract

Facial expressions are a form of non-verbal communication, they appear as changes on the surface of the facial skin according to one's inner emotional states, aims, or social communications. Classification of these expressions is a normal process for humans, but it is a challenging task for machines.
Lately, interest in facial expression recognition has grown, and many systems have been developed to classify expressions from facial images. Any expression recognition system is comprised of three steps. The first one is face acquisition, then feature extraction, and finally classification. The classification accuracy depends primarily on the feature extraction step.  Therefore, in this research we study many texture feature extraction descriptors and compare their results under the same preprocessing circumstances; moreover, we propose two improvements for one of these descriptors, which give better results than the original one. We validate the results on two commonly used databases for expression recognition using Matlab programming language, wishing all of that to be an interesting point for researchers in this field.

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Published

31-12-2021

How to Cite

Haj Najeb, A. N., & Nasser, N. (2021). Facial Expression Recognition Based on Texture Features. Al-Nahrain Journal for Engineering Sciences, 24(2), 144–148. https://doi.org/10.29194/NJES.24020144