Near Infrared Face Recognition: A Comparison of Moment-Based Approaches

  • Sajad Farokhi
  • Siti Mariyam Shamsuddin
  • U. U. Sheikh
  • Jan Flusser
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 291)

Abstract

Moment based methods have evolved into a powerful tool for face recognition applications. In this paper, a comparative study on moments based feature extraction methods in terms of their capability to recognize facial images with different challenges is done to evaluate the performance of different type of moments. The moments include Geometric moments (GM’s), Zernike moments (ZM’s), Pseudo-Zernike moments (PZM’s) and Wavelet moments (WM’s). Experiments conducted on CASIA NIR database showed that Zernike moments outperformed other moment-based methods for facial images with different challenges such as facial expressions, head pose and noise.

Keywords

Moments Near infrared Comparative study Face recognition 

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Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  • Sajad Farokhi
    • 1
  • Siti Mariyam Shamsuddin
    • 1
  • U. U. Sheikh
    • 2
  • Jan Flusser
    • 3
  1. 1.Soft Computing Research Group, Faculty of ComputingUniversiti Teknologi MalaysiaJohor BahruMalaysia
  2. 2.Faculty of Electrical EngineeringUniversiti Teknologi MalaysiaJohor BahruMalaysia
  3. 3.Institute of Information Theory and Automation of the Academy of Sciences of the Czech RepublicPragueCzech Republic

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