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Face Recognition by RBF with Wavelet, DCV and Modified LBP Operator Face Representation Methods

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Mining Intelligence and Knowledge Exploration (MIKE 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10682))

Abstract

A face recognition system must be robust with respect to many variability such as viewpoint, illumination, and facial expression of the face image. The main aim of the proposed work is to represent and recognize face images with different poses. An efficient face recognition system with face image representation using wavelet and averaged wavelet packet coefficients in the form of Discriminative Common Vector (DCV) and modified Local Binary Patterns (LBP) and recognition using radial basis function (RBF) neural network is presented. Face images are decomposed by 2-level two-dimensional (2-D) wavelet and wavelet packet transformation. The discriminative common vectors are obtained for wavelet and averaged wavelet packet coefficients. Newly proposed LBP operator is applied on the DCV and LBPs are obtained. Histogram values are generated for the LBP and recognized using RBF network. The proposed work is tested on three standard face databases namely Olivetti-Oracle Research Lab (ORL), Japanese Female Facial Expression (JAFFE) and Essex face database. The extracted features are recognized by the proposed method results in good recognition rates. The execution time for the proposed methods is also less because of the meaningful extracted features obtained from the face representation methods.

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Authors and Affiliations

  1. Department of Computer Science, ANJA College, Sivakasi, Tamilnadu, India

    J. Jebakumari Beulah Vasanthi

  2. Department of Computer Science, VHNSN College, Virudhunagar, Tamilnadu, India

    T. Kathirvalavakumar

Authors
  1. J. Jebakumari Beulah Vasanthi
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  2. T. Kathirvalavakumar
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Corresponding authors

Correspondence to J. Jebakumari Beulah Vasanthi or T. Kathirvalavakumar .

Editor information

Editors and Affiliations

  1. Indian Statistical Institute, Kolkata, India

    Ashish Ghosh

  2. Institute for Development and Research in Banking Technology, Hyderabad, India

    Rajarshi Pal

  3. Indian Institute of Information Technology, Sri City, India

    Rajendra Prasath

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Jebakumari Beulah Vasanthi, J., Kathirvalavakumar, T. (2017). Face Recognition by RBF with Wavelet, DCV and Modified LBP Operator Face Representation Methods. In: Ghosh, A., Pal, R., Prasath, R. (eds) Mining Intelligence and Knowledge Exploration. MIKE 2017. Lecture Notes in Computer Science(), vol 10682. Springer, Cham. https://doi.org/10.1007/978-3-319-71928-3_18

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  • DOI: https://doi.org/10.1007/978-3-319-71928-3_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71927-6

  • Online ISBN: 978-3-319-71928-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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