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Reseach Article

Image Retrieval and Image Categorization by Content based Information

Published on November 2012 by M. Kalaiselvi, M. Malathi
International Conference on Electronics, Communication and Information systems
Foundation of Computer Science USA
ICECI - Number 1
November 2012
Authors: M. Kalaiselvi, M. Malathi
1e524145-d091-499f-b5d9-7c5d5e26a6c0

M. Kalaiselvi, M. Malathi . Image Retrieval and Image Categorization by Content based Information. International Conference on Electronics, Communication and Information systems. ICECI, 1 (November 2012), 1-5.

@article{
author = { M. Kalaiselvi, M. Malathi },
title = { Image Retrieval and Image Categorization by Content based Information },
journal = { International Conference on Electronics, Communication and Information systems },
issue_date = { November 2012 },
volume = { ICECI },
number = { 1 },
month = { November },
year = { 2012 },
issn = 0975-8887,
pages = { 1-5 },
numpages = 5,
url = { /specialissues/iceci/number1/9456-1002/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 International Conference on Electronics, Communication and Information systems
%A M. Kalaiselvi
%A M. Malathi
%T Image Retrieval and Image Categorization by Content based Information
%J International Conference on Electronics, Communication and Information systems
%@ 0975-8887
%V ICECI
%N 1
%P 1-5
%D 2012
%I International Journal of Computer Applications
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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Index Terms

Computer Science
Information Sciences

Keywords

Content Based Image Retrieval (cbir) Scale Invariant Feature Transform (sift) Image Features Haar Wavelet And D4 Wavelet