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Improving textures discrimination in the local binary patterns techniques by using symmetry & group theory

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Abstract
The underlying working mechanism of Local Binary Pattern (LBP) techniques is still a topic to investigate. In this paper we explore symmetry & group theory for grouping functions that represent binary intensity changes obtained with the LBP technique. This additionally offers a strong mathematical foundation for the basis of the technique. We include complement and mirror invariants to the known LBP rotational invariant. We tested our algorithm using 13 textures from the Brodatz database. The statistical analysis shows that combining rotational, mirrored and complemented versions of local texture results in an improvement in the performance of the technique in terms of accuracy describing textures and discrimination distinguishing textures.
Keywords
texture symmetry, LBP technique, texture representation, texture discrimination

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Chicago
Orjuela Vargas, Sergio Alejandro, Rolando Augusto Quiñones Lara, Benhur Ortiz Jaramillo, Filip Rooms, Robain De Keyser, and Wilfried Philips. 2011. “Improving Textures Discrimination in the Local Binary Patterns Techniques by Using Symmetry & Group Theory.” In 2011 17th International Conference on Digital Signal Processing. New York, NY, USA: IEEE.
APA
Orjuela Vargas, S. A., Quiñones Lara, R. A., Ortiz Jaramillo, B., Rooms, F., De Keyser, R., & Philips, W. (2011). Improving textures discrimination in the local binary patterns techniques by using symmetry & group theory. 2011 17th International conference on digital signal processing. Presented at the 17th International conference on Digital Signal Processing (DSP 2011), New York, NY, USA: IEEE.
Vancouver
1.
Orjuela Vargas SA, Quiñones Lara RA, Ortiz Jaramillo B, Rooms F, De Keyser R, Philips W. Improving textures discrimination in the local binary patterns techniques by using symmetry & group theory. 2011 17th International conference on digital signal processing. New York, NY, USA: IEEE; 2011.
MLA
Orjuela Vargas, Sergio Alejandro, Rolando Augusto Quiñones Lara, Benhur Ortiz Jaramillo, et al. “Improving Textures Discrimination in the Local Binary Patterns Techniques by Using Symmetry & Group Theory.” 2011 17th International Conference on Digital Signal Processing. New York, NY, USA: IEEE, 2011. Print.
@inproceedings{1856634,
  abstract     = {The underlying working mechanism of Local Binary Pattern (LBP) techniques is still a topic to investigate. In this paper we explore symmetry \& group theory for grouping functions that represent binary intensity changes obtained with the LBP technique. This additionally offers a strong mathematical foundation for the basis of the technique. We include complement and mirror invariants to the known LBP rotational invariant. We tested our algorithm using 13 textures from the Brodatz database. The statistical analysis shows that combining rotational, mirrored and complemented versions of local texture results in an improvement in the performance of the technique in terms of accuracy describing textures and discrimination distinguishing textures.},
  articleno    = {F3C3},
  author       = {Orjuela Vargas, Sergio Alejandro and Qui{\~n}ones Lara, Rolando Augusto and Ortiz Jaramillo, Benhur and Rooms, Filip and De Keyser, Robain and Philips, Wilfried},
  booktitle    = {2011 17th International conference on digital signal processing},
  isbn         = {9781457702723},
  keyword      = {texture symmetry,LBP technique,texture representation,texture discrimination},
  language     = {eng},
  location     = {Corfu, Greece},
  pages        = {6},
  publisher    = {IEEE},
  title        = {Improving textures discrimination in the local binary patterns techniques by using symmetry \& group theory},
  url          = {http://dx.doi.org/10.1109/ICDSP.2011.6004978},
  year         = {2011},
}

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