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A 3D–2D face recognition method based on extended Gabor wavelet combining curvature and edge detection

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Abstract

The main limitation in 3D face recognition (FR) systems is their susceptibility to scanning difficulties and uncontrolled environments such as pose, illumination and expression variety. This paper proposes a new FR framework based on 3D to 2D mesh deforming and combined Gabor curvature and edge maps. The advantage of this method comes from the powerful saliency distribution achieved from applying extended Gabor wavelets to 2D projected face meshes. The extracted feature vectors are classified using the outstanding robustness of the support vector machine. Experiments carried out on common databases proved that valid accuracy rates can be accomplished by the proposed approach comparing to other existing methods.

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Authors and Affiliations

  1. Laboratory EμE, Faculty of Sciences of Monastir, Monastir, Tunisia

    Ghada Torkhani, Anis Ladgham & Mohamed Nejib Mansouri

  2. Department of Electrical Engineering, National Engineering School of Monastir (ENIM), Monastir, Tunisia

    Anis Sakly & Mohamed Nejib Mansouri

  3. Reseach Unit, Industrial Systems Study and Renewable Energy (ESIER), ENIM, Monastir, Tunisia

    Ghada Torkhani & Anis Sakly

Authors
  1. Ghada Torkhani
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  2. Anis Ladgham
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  3. Anis Sakly
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  4. Mohamed Nejib Mansouri
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Correspondence to Anis Ladgham.

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Torkhani, G., Ladgham, A., Sakly, A. et al. A 3D–2D face recognition method based on extended Gabor wavelet combining curvature and edge detection. SIViP 11, 969–976 (2017). https://doi.org/10.1007/s11760-016-1046-7

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  • DOI: https://doi.org/10.1007/s11760-016-1046-7

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