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A Performance Evaluation of Different Texture Models for Image Indexing and Retrieval

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IJCA Proceedings on National Conference on Research Issues in Image Analysis and Mining Intelligence
© 2015 by IJCA Journal
NCRIIAMI 2015 - Number 2
Year of Publication: 2015
Authors:
S. Pannirselvam
K. Selvarajan

S.pannirselvam and K.selvarajan. Article: A Performance Evaluation of Different Texture Models for Image Indexing and Retrieval. IJCA Proceedings on National Conference on Research Issues in Image Analysis and Mining Intelligence NCRIIAMI 2015(2):1-4, June 2015. Full text available. BibTeX

@article{key:article,
	author = {S.pannirselvam and K.selvarajan},
	title = {Article: A Performance Evaluation of Different Texture Models for Image Indexing and Retrieval},
	journal = {IJCA Proceedings on National Conference on Research Issues in Image Analysis and Mining Intelligence},
	year = {2015},
	volume = {NCRIIAMI 2015},
	number = {2},
	pages = {1-4},
	month = {June},
	note = {Full text available}
}

Abstract

In recent years, image mining techniques enters and plays a vital role in various fields. Due to the rapid development in the information technology various techniques has been emerged to process and store these information, issues in data retrieval and recognition remains continued owing to its immense voluminous. Image retrieval has been developed into a very active research area specializing on how to extract and retrieve the images. The various methods have been proposed for image retrieval and each method has advantages and drawbacks. The complexity in process and other issues affects performance of existing system which makes existing system is insufficient. In this paper image retrieval with feature vector calculates the threshold value separately and stored in feature database. The feature is generated and matching is done by Chi-square classification which is used to measure distance between two images. The experimental result shows that MBLBP method provides better retrieval rate when compared with the existing methods such as Local Binary Pattern, Elongated Local Binary Pattern Template Method.

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