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Structural similarity classifier for facial expression recognition

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Abstract

A novel Gabor filter structural similarity algorithm (GFSSIM) is proposed for facial expression recognition (FER) on noisy images. Low-resolution facial images with low SNRs are specifically dealt with FER system. The features are extracted using 40 Gabor filters, and a feature subset is selected for classification. The test image is classified based on proposed GFSSIM algorithm. The experimental results show that the recognition rate for heavily deteriorated images outperforms the conventional classifier method. In addition, the proposed method is more efficient from the computational complexity point of view.

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Authors and Affiliations

  1. Electrical and Computer Engineering, RMIT University, Melbourne, Australia

    Seyed Mehdi Lajevardi

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  1. Seyed Mehdi Lajevardi
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Correspondence to Seyed Mehdi Lajevardi.

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Lajevardi, S.M. Structural similarity classifier for facial expression recognition. SIViP 8, 1103–1110 (2014). https://doi.org/10.1007/s11760-014-0639-2

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  • DOI: https://doi.org/10.1007/s11760-014-0639-2

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