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Multiple Image Characterization Techniques for Enhanced Facial Expression Recognition

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Intelligent Systems Technologies and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 384))

Abstract

This paper describes an enhanced facial expression recognition system. In the first step, the face localization is done using a simplified method, then the facial components are extracted and described by three feature vectors: the Zernike moments, the spectral components’ distribution through the DCT transform and by LBP features. The different feature vectors are used separately then combined to train back-propagation neural networks which are used in the facial expression recognition step. A subset feature selection algorithm was applied to these combined feature vectors in order to make dimensionality reduction and to improve the facial expression recognition process. Experiments performed on the JAFFE database along with comparisons to other methods have affirmed the validity and the good performances of the proposed approach.

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Author information

Authors and Affiliations

  1. Département de Génie-Electrique, Université M.C.M Souk-Ahras, Souk-Ahras, Algeria

    Mohammed Saaidia

  2. Département d’ Electronique, Université Badji-Mokhtar de Annaba, Annaba, Algeria

    Narima Zermi & Messaoud Ramdani

Authors
  1. Mohammed Saaidia
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  2. Narima Zermi
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  3. Messaoud Ramdani
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Corresponding author

Correspondence to Mohammed Saaidia .

Editor information

Editors and Affiliations

  1. Dipartimento di Ingegneria dell’ Informazione (DINFO) , Universita degli Studi di Firenze, Firenze, Italy

    Stefano Berretti

  2. School of CS/IT, Indian Institute of Information Tech. and Management – Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  3. Indian Institute of Management Rohtak, Rohtak, Haryana, India

    Praveen Ranjan Srivastava

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Saaidia, M., Zermi, N., Ramdani, M. (2016). Multiple Image Characterization Techniques for Enhanced Facial Expression Recognition. In: Berretti, S., Thampi, S., Srivastava, P. (eds) Intelligent Systems Technologies and Applications. Advances in Intelligent Systems and Computing, vol 384. Springer, Cham. https://doi.org/10.1007/978-3-319-23036-8_43

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  • DOI: https://doi.org/10.1007/978-3-319-23036-8_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23035-1

  • Online ISBN: 978-3-319-23036-8

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