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Selective local texture features based face recognition with single sample per class

Journal of the Brazilian Computer Society volume 18, pages 229–235 (2012)Cite this article

Abstract

Local appearance-based methods have been successfully applied to face recognition and achieved state-of-the-art performance. In this paper we propose a local selective feature extraction approach based on Gabor filters and the Local Binary Pattern (LBP) approach to face recognition. A Gabor filter extracts the textural features from the face image and generates the binary face template using those features. The binary face template acts like a mask to extract the local texture information of the face image using a Local Binary Pattern technique. This selective local texture feature approach uses the histogram-based matching for face recognition. This method reduces the computation time considerably. This method also reduces the number of Local Binary Patterns into half compared to the existing LBP method. This proposed approach reduces the computation time for the FERET dataset by 45%. Experiments on well-known face databases such as FERET, Yale, Indian Faces and ORL show that this approach obtains consistent and promising results in the scenario of one training sample per person with significant facial variation.

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Authors and Affiliations

  1. Research Scholar, Department of Computer Science, Mother Teresa Women’s University Kodaikanal, Kodaikanal, 624102, India

    K. Jaya Priya

  2. Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tirunelveli, 627012, Tamilnadu, India

    R. S. Rajesh

Authors
  1. K. Jaya Priya
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  2. R. S. Rajesh
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Correspondence to K. Jaya Priya.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Jaya Priya, K., Rajesh, R.S. Selective local texture features based face recognition with single sample per class. J Braz Comput Soc 18, 229–235 (2012). https://doi.org/10.1007/s13173-011-0049-z

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