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International Joint Conference on Advances in Signal Processing and Information Technology

SPIT 2012: Signal Processing and Information Technology pp 137–143Cite as

Evaluation of CIE-XYZ System for Face Recognition Using Kernel-PCA

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Abstract

paper evaluates the performance of face recognition with different CIE color spaces. The XYZ and L*a*b* color spaces are compared with the gray image (luminance information Y). The face recognition system consists of a feature extraction step and a classification step. The Kernel-PCA is used to construct the feature space. Kernel-PCA is a nonlinear form of Principal Component Analysis (PCA). The k-nearest neighbor classifier with cosine measure is used in the classification step. Experiments using FEI color database with 200 subjects, show that the b* color component can improve the recognition rate.

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Author information

Authors and Affiliations

  1. Scientific Computing Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

    Hala M. Ebied

Authors
  1. Hala M. Ebied
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Editor information

Editors and Affiliations

  1. Network Security Group, Institute of Doctors Engineering and Scientists (The IDES), 695 004, Kerala, India

    Vinu V. Das

  2. Mathematics and Computer Science, Menoufia University, Cairo, Egypt

    Passent Elkafrawy

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© 2014 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Ebied, H.M. (2014). Evaluation of CIE-XYZ System for Face Recognition Using Kernel-PCA. In: Das, V.V., Elkafrawy, P. (eds) Signal Processing and Information Technology. SPIT 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 117. Springer, Cham. https://doi.org/10.1007/978-3-319-11629-7_20

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  • DOI: https://doi.org/10.1007/978-3-319-11629-7_20

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11628-0

  • Online ISBN: 978-3-319-11629-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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