Texture Feature Extraction Research Based on GLCM-CLBP Algorithm

DOI

10.2991/emim-17.2017.36How to use a DOI?

Keywords

Texture feature; CLBP algorithm; GLCM; Feature parameters

Abstract

In view of the existing texture feature extraction method of computational complexity and accuracy problems, this paper proposes a calculation method fused with Complete Local Binary Patterns (CLBP) and Gray-level Co-occurrence Matrix (GLCM). This method uses the rotation invariant CLBP operator to process the texture image and get the CLBP image, then calculate the GLCM of the CLBP image, use the contrast, correlation, energy and inverse difference moment to describe the image texture feature. The experimental results show that the method can reduce the feature parameters at the same time, also improved the texture description ability.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xuejing Ding
PY  - 2017/04
DA  - 2017/04
TI  - Texture Feature Extraction Research Based on GLCM-CLBP Algorithm
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 167
EP  - 171
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.36
DO  - 10.2991/emim-17.2017.36
ID  - Ding2017/04
ER  -