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The Geometric Local Textural Patterns (GLTP) technique

Sergio Alejandro Orjuela Vargas UGent, Juan Pablo Yañez and Wilfried Philips UGent (2014) Local binary patterns : new variants and new applications. In Studies in Computational Intelligence 506. p.30-70
abstract
In this chapter we present a family of techniques based on the principle of the Local Binary Pattern (LBP) technique. This family is called the Geometric Local Textural Patterns (GLTP). Classical LBP techniques are based on exploring intensity changes around each pixel in an image using close neighbourhoods. The main novelty of the GLTP techniques is that they explores intensity changes on oriented neighbourhoods instead of on close neighbourhoods. An oriented neighbourhood describes a particular geometry composed of points on circles with different radii around the center pixel. A digital representation of the points on the oriented neighbourhood defines a GLTP-code. Symmetric versions of the geometries around the pixel are assessed the same GLTP code. Each pixel in the image is assigned a set of GLTP-codes, each for a particular geometry. The texture of an image is characterized with a GLTP histogram of the occurrences of the GLTP-codes on the whole image. We explain the principle of the techniques using the simplest case, called the Geometric Local Binary (GLBP) technique, which is based on boolean comparisons. Then we present variations of this technique to enlarge the family of GLTP techniques. We quantify the texture difference between a pair or images or regions by computing the divergence between their corresponding GLTP-histograms using an adaptation of the Jensen-Shannon entropy.
Please use this url to cite or link to this publication:
author
organization
year
type
bookChapter
publication status
published
subject
keyword
image processing, LBP, Texture
book title
Local binary patterns : new variants and new applications
editor
Sheryl brahnam, Lakhmi C. Jain, Loris Nanni and Alessandra Lumini
series title
Studies in Computational Intelligence
volume
506
edition
1
pages
30 - 70
publisher
Springer
place of publication
Heidelberg, Germany
ISSN
1860-949X
ISBN
9783642392887
language
English
UGent publication?
yes
classification
B2
copyright statement
I have transferred the copyright for this publication to the publisher
id
3225212
handle
http://hdl.handle.net/1854/LU-3225212
alternative location
http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-642-39288-7
date created
2013-05-27 14:19:38
date last changed
2017-01-02 09:54:54
@incollection{3225212,
  abstract     = {In this chapter we present a family of techniques based on the principle of the Local Binary Pattern (LBP) technique. This family is called the Geometric Local Textural Patterns (GLTP). Classical LBP techniques are based on exploring intensity changes around each pixel in an image using close neighbourhoods. The main novelty of the GLTP techniques is that they explores intensity changes on oriented neighbourhoods instead of on close neighbourhoods. An oriented neighbourhood describes a particular geometry composed of points on circles with different radii around the center pixel. A digital representation of the points on the oriented neighbourhood defines a GLTP-code. Symmetric versions of the geometries around the pixel are assessed the same GLTP code. Each pixel in the image is assigned a set of GLTP-codes, each for a particular geometry. The texture of an image is characterized with a GLTP histogram of the occurrences of the GLTP-codes on the whole image. We explain the principle of the techniques using the simplest case, called the Geometric Local Binary (GLBP) technique, which is based on boolean comparisons. Then we present variations of this technique to enlarge the family of GLTP techniques. We quantify the texture difference between a pair or images or regions by computing the divergence between their corresponding GLTP-histograms using an adaptation of the Jensen-Shannon entropy.},
  author       = {Orjuela Vargas, Sergio Alejandro and Ya{\~n}ez, Juan Pablo and Philips, Wilfried},
  booktitle    = {Local binary patterns : new variants and new applications},
  editor       = {brahnam, Sheryl and Jain, Lakhmi C. and Nanni, Loris  and Lumini, Alessandra},
  isbn         = {9783642392887},
  issn         = {1860-949X},
  keyword      = {image processing,LBP,Texture},
  language     = {eng},
  pages        = {30--70},
  publisher    = {Springer},
  series       = {Studies in Computational Intelligence},
  title        = {The Geometric Local Textural Patterns (GLTP) technique},
  url          = {http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-642-39288-7},
  volume       = {506},
  year         = {2014},
}

Chicago
Orjuela Vargas, Sergio Alejandro, Juan Pablo Yañez, and Wilfried Philips. 2014. “The Geometric Local Textural Patterns (GLTP) Technique.” In Local Binary Patterns : New Variants and New Applications, ed. Sheryl brahnam, Lakhmi C. Jain, Loris Nanni, and Alessandra Lumini, 506:30–70. 1st ed. Heidelberg, Germany: Springer.
APA
Orjuela Vargas, S. A., Yañez, J. P., & Philips, W. (2014). The Geometric Local Textural Patterns (GLTP) technique. In S. brahnam, L. C. Jain, L. Nanni, & A. Lumini (Eds.), Local binary patterns : new variants and new applications (1st ed., Vol. 506, pp. 30–70). Heidelberg, Germany: Springer.
Vancouver
1.
Orjuela Vargas SA, Yañez JP, Philips W. The Geometric Local Textural Patterns (GLTP) technique. In: brahnam S, Jain LC, Nanni L, Lumini A, editors. Local binary patterns : new variants and new applications. 1st ed. Heidelberg, Germany: Springer; 2014. p. 30–70.
MLA
Orjuela Vargas, Sergio Alejandro, Juan Pablo Yañez, and Wilfried Philips. “The Geometric Local Textural Patterns (GLTP) Technique.” Local Binary Patterns : New Variants and New Applications. 1st ed. Ed. Sheryl brahnam et al. Vol. 506. Heidelberg, Germany: Springer, 2014. 30–70. Print.