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Extended Rule Based Local Binary Pattern Technique for Texture Classification and Analysis

O. Rama Devi*, E. V. Prasad**, L. S. S. Reddy***

* Assistant Professor, Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada.

** Director, Lakireddy Bali Reddy College of Engineering, Mylavaram.

*** Pro.Vice Chancellor, K.L University, Vaddeswaram.

Periodicity:March - May'2014
DOI : https://doi.org/10.26634/jpr.1.1.2822

Abstract

Texture analysis is one of the important and most useful tasks in image processing applications. Several texture models have been developed over the past few years and Local Binary Patterns (LBP) are one of the simple and efficient approaches among them. The main disadvantage of “LBP” method is the complex computation of vector generation. Here an innovative classifier, called Extended Rule Based Local Binary Pattern (ERLBP) is given, which is an efficient model and its performance has been compared with other widely used texture models to show the computational superiority, robustness to gray scale variations and improved discriminating capability.

Keywords

Local Binary Patterns, Texture Analysis, Texture Classification, RLBP.

How to Cite this Article?

Devi, O. R., Prasad, E. V., and Reddy, L. S. S. (2014). Extended Rule Based Local Binary Pattern Technique For Texture Classification And Analysis. i-manager’s Journal on Pattern Recognition, 1(1), 30-35. https://doi.org/10.26634/jpr.1.1.2822

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