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Recognizing Avatar Faces Using Wavelet-Based Adaptive Local Binary Patterns with Directional Statistical Features

  • Conference paper
Transactions on Computational Science XVIII

Part of the book series: Lecture Notes in Computer Science ((TCOMPUTATSCIE,volume 7848))

Abstract

In this paper, a novel face recognition technique based on discrete wavelet transform and Adaptive Local Binary Pattern (ALBP) with directional statistical features is proposed. The proposed technique consists of three stages: preprocessing, feature extraction and recognition. In preprocessing and feature extraction stages, wavelet decomposition is used to enhance the common features of the same subject of images and the ALBP is used to extract representative features from each facial image. Then, the mean and the standard deviation of the local absolute difference between each pixel and its neighbors are used within ALBP and the nearest neighbor classifier to improve the classification accuracy of the LBP. Experiments conducted on two virtual world avatar face image datasets show that our technique performs better than LBP, PCA, multi-scale Local Binary Pattern, ALBP and ALBP with directional statistical features (ALBPF) in terms of accuracy and the time required to classify each facial image to its subject.

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Author information

Authors and Affiliations

  1. Computer Engineering and Computer Science, University of Louisville, Louisville, KY, 40292, USA

    Abdallah A. Mohamed & Roman V. Yampolskiy

  2. Department of Computer Science, University of Calgary, Calgary, Alberta, T2N1N4, Canada

    Marina L. Gavrilova

  3. Department of Mathematics, Menoufia University, Shebin El-Koom, Menoufia, 32511, Egypt

    Abdallah A. Mohamed

Authors
  1. Abdallah A. Mohamed
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  2. Marina L. Gavrilova
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  3. Roman V. Yampolskiy
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  2. Exascala Ltd., Unit 9, 97 Rickman Drive, B15 2AL, Birmingham, UK

    C. J. Kenneth Tan

  3. Institut für Graphische Datenverarbeitung, Fraunhofer Gesellschaft, Fraunhoferstraße 5, 64283, Darmstadt, Germany

    Arjan Kuijper

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Mohamed, A.A., Gavrilova, M.L., Yampolskiy, R.V. (2013). Recognizing Avatar Faces Using Wavelet-Based Adaptive Local Binary Patterns with Directional Statistical Features. In: Gavrilova, M.L., Tan, C.J.K., Kuijper, A. (eds) Transactions on Computational Science XVIII. Lecture Notes in Computer Science, vol 7848. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38803-3_8

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  • DOI: https://doi.org/10.1007/978-3-642-38803-3_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38802-6

  • Online ISBN: 978-3-642-38803-3

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