|
Abstract
|
Article Information:
A Statistical Approach of Texton Based Texture Classification Using LPboosting Classifier
C. Vivek and S. Audithan
Corresponding Author: C. Vivek
Submitted: December 04, 2013
Accepted: January 01, 2014
Published: May 15, 2014 |
Abstract:
|
The aim of the study in this research deals with the accurate texture classification and the image texture analysis has a voluminous errand prospective in real world applications. In this study, the texton co-occurrence matrix applied to the Broadatz database images that derive the template texton grid images and it undergoes to the discrete shearlet transform to decompose the image. The entropy lineage parameters of redundant and interpolate at a certain point which congregating adjacent regions based on geometric properties then the classification is apprehended by comparing the similarity between the estimated distributions of all detail sub bands through the strong LP boosting classification with various weak classifier configurations. We show that the resulted texture features while incurring the maximum of the discriminative information. Our hybrid classification method significantly outperforms the existing texture descriptors and stipulates classification accuracy in the state-of-the-art real world imaging applications.
Key words: LPboost classifier, shearlet transform, texton co-occurrence matrix, texture image classification, weak classification, ,
|
|
Abstract
|
PDF
|
HTML |
|
Cite this Reference:
C. Vivek and S. Audithan, . A Statistical Approach of Texton Based Texture Classification Using LPboosting Classifier. Research Journal of Applied Sciences, Engineering and Technology, (19): 4088-4094.
|
|
|
|
 |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
 |
| Information |
|
|
|
|
| Sales & Services |
|
|
|
|
