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A Hybrid Approach for Facial Expression Recognition Using Extended Local Binary Patterns and Principal Component Analysis

A Hybrid Approach for Facial Expression Recognition Using Extended Local Binary Patterns and Principal Component Analysis

Gopal Krishan Prajapat, Rakesh Kumar
Copyright: © 2019 |Volume: 8 |Issue: 2 |Pages: 25
ISSN: 2578-7551|EISSN: 2578-7543|EISBN13: 9781522575382|DOI: 10.4018/IJECME.2019070101
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MLA

Prajapat, Gopal Krishan, and Rakesh Kumar. "A Hybrid Approach for Facial Expression Recognition Using Extended Local Binary Patterns and Principal Component Analysis." IJECME vol.8, no.2 2019: pp.1-25. http://doi.org/10.4018/IJECME.2019070101

APA

Prajapat, G. K. & Kumar, R. (2019). A Hybrid Approach for Facial Expression Recognition Using Extended Local Binary Patterns and Principal Component Analysis. International Journal of Electronics, Communications, and Measurement Engineering (IJECME), 8(2), 1-25. http://doi.org/10.4018/IJECME.2019070101

Chicago

Prajapat, Gopal Krishan, and Rakesh Kumar. "A Hybrid Approach for Facial Expression Recognition Using Extended Local Binary Patterns and Principal Component Analysis," International Journal of Electronics, Communications, and Measurement Engineering (IJECME) 8, no.2: 1-25. http://doi.org/10.4018/IJECME.2019070101

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Abstract

Facial feature extraction and recognition plays a prominent role in human non-verbal interaction and it is one of the crucial factors among pose, speech, facial expression, behaviour and actions which are used in conveying information about the intentions and emotions of a human being. In this article an extended local binary pattern is used for the feature extraction process and a principal component analysis (PCA) is used for dimensionality reduction. The projections of the sample and model images are calculated and compared by Euclidean distance method. The combination of extended local binary pattern and PCA (ELBP+PCA) improves the accuracy of the recognition rate and also diminishes the evaluation complexity. The evaluation of proposed facial expression recognition approach will focus on the performance of the recognition rate. A series of tests are performed for the validation of algorithms and to compare the accuracy of the methods on the JAFFE, Extended Cohn-Kanade images database.

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