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Local binary patterns versus signal processing texture analysis: a study from a performance evaluation perspective

Ovidiu Ghita (School of Electronic Engineering, Dublin City University, Dublin, Ireland)
Dana Ilea (School of Electronic Engineering, Dublin City University, Dublin, Ireland)
Antonio Fernandez (School of Industrial Engineering, University of Vigo, Vigo, Spain)
Paul Whelan (School of Electronic Engineering, Dublin City University, Dublin, Ireland)

Sensor Review

ISSN: 0260-2288

Article publication date: 23 March 2012

315

Abstract

Purpose

The purpose of this paper is to review and provide a detailed performance evaluation of a number of texture descriptors that analyse texture at micro‐level such as local binary patterns (LBP) and a number of standard filtering techniques that sample the texture information using either a bank of isotropic filters or Gabor filters.

Design/methodology/approach

The experimental tests were conducted on standard databases where the classification results are obtained for single and multiple texture orientations. The authors also analysed the performance of standard filtering texture analysis techniques (such as those based of LM and MR8 filter banks) when applied to the classification of texture images contained in standard Outex and Brodatz databases.

Findings

The most important finding resulting from this study is that although the LBP/C and the multi‐channel Gabor filtering techniques approach texture analysis from a different theoretical perspective, in this paper the authors have experimentally demonstrated that they share some common properties in regard to the way they sample the macro and micro properties of the texture.

Practical implications

Texture is a fundamental property of digital images and the development of robust image descriptors plays a crucial role in the process of image segmentation and scene understanding.

Originality/value

This paper contrast, from a practical and theoretical standpoint, the LBP and representative multi‐channel texture analysis approaches and a substantial number of experimental results were provided to evaluate their performance when applied to standard texture databases.

Keywords

Citation

Ghita, O., Ilea, D., Fernandez, A. and Whelan, P. (2012), "Local binary patterns versus signal processing texture analysis: a study from a performance evaluation perspective", Sensor Review, Vol. 32 No. 2, pp. 149-162. https://doi.org/10.1108/02602281211209446

Publisher

:

Emerald Group Publishing Limited

Copyright © 2012, Emerald Group Publishing Limited

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