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Local Binary Patterns: New Variants and Applications pp 17–46Cite as

A Unifying Framework for LBP and Related Methods

Part of the Studies in Computational Intelligence book series (SCI,volume 506)

Abstract

In this chapter we describe a unifying framework for local binary patterns and variants which we refer to as histograms of equivalent patterns (HEP). In presenting this concept we discuss some basic issues in texture analysis: the problem of defining what texture is; the problem of classifying the many existing texture descriptors; the concept of bag-of-features and the design choices that one has to deal with when designing a texture descriptor. We show how this relates to local binary patterns and related methods and propose a unifying mathematical formalism to express them within the HEP. Finally, we give a geometrical interpretation of these methods as partitioning operators in a high-dimensional space, showing how this representation can propound possible directions for future research.

Keywords

  • Kernel Function
  • Feature Space
  • Local Binary Pattern
  • Texture Descriptor
  • Image Patch

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Acknowledgments

This work was supported by the Spanish Government under projects no. TRA2011-29454-C03-01 and CTM2010-16573.

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Authors and Affiliations

  1. Department of Industrial Engineering, Università degli Studi di Perugia, Via G. Duranti, 67-06125 , Perugia, Italy

    Francesco Bianconi

  2. School of Industrial Engineering, Universidade de Vigo, Campus Universitario, 36310 , Vigo, Spain

    Antonio Fernández

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  1. Francesco Bianconi
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Correspondence to Francesco Bianconi .

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Editors and Affiliations

  1. Computer Information Systems, Missouri State University, Springfield, USA

    Sheryl Brahnam

  2. Faculty of Education, Science, Technology & Mathematics, University of Canberra, Canberra, Australia

    Lakhmi C. Jain

  3. Departimento di Elettronica e Informatica (DEI), Università di Padova, Padua, Italy

    Loris Nanni

  4. DEIS University of Bologna, Cesena, Italy

    Alessandra Lumini

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Bianconi, F., Fernández, A. (2014). A Unifying Framework for LBP and Related Methods. In: Brahnam, S., Jain, L., Nanni, L., Lumini, A. (eds) Local Binary Patterns: New Variants and Applications. Studies in Computational Intelligence, vol 506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39289-4_2

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