Image Retrieval and Image Categorization by Content based Information

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IJCA Special Issue on International Conference on Electronics, Communication and Information systems
© 2012 by IJCA Journal
ICECI - Number 1
Year of Publication: 2012
Authors:
M. Kalaiselvi
M. Malathi

M Kalaiselvi and M Malathi. Article: Image Retrieval and Image Categorization by Content based Information. IJCA Special Issue on International Conference on Electronics, Communication and Information systems ICECI(1):1-5, November 2012. Full text available. BibTeX

@article{key:article,
	author = {M. Kalaiselvi and M. Malathi},
	title = {Article: Image Retrieval and Image Categorization by Content based Information},
	journal = {IJCA Special Issue on International Conference on Electronics, Communication and Information systems},
	year = {2012},
	volume = {ICECI},
	number = {1},
	pages = {1-5},
	month = {November},
	note = {Full text available}
}

Abstract

Fast retrieval of images from database is done by unsupervised image categorization technique. CBIR effectiveness is based on the image categorization. For image categorization technique, the image features are extracted by using Scale Invariant Feature Transform (SIFT). Image Categorization and Content-Based Image Retrieval (CBIR) allows automatic extraction of target images according to object feature contents of the image itself. Haar Transform is used to decompose color images into multilevel scale. D4 wavelet Transform is used for the conversion of wavelet coefficients. A progressive image retrieval strategy is achieved by flexible CBIR. In terms of recall rate and retrieval speed, the retrieval performance of D4 and Haar wavelet is compared with its wavelet histograms. Efficient retrieval can be achieved experimentally and the results can be reflected in the form of CBIR wavelets. Image Retrieval system is a system for searching and retrieving similar images from a large database of digital images. Images are ranked based on their similarities.

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