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Content based Image Retrieval using Sectorisation of Self Mutated Hybrid Wavelet Transforms

by Yogita D. Shinde, Sudeep D. Thepade
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 24
Year of Publication: 2015
Authors: Yogita D. Shinde, Sudeep D. Thepade
10.5120/21408-4419

Yogita D. Shinde, Sudeep D. Thepade . Content based Image Retrieval using Sectorisation of Self Mutated Hybrid Wavelet Transforms. International Journal of Computer Applications. 120, 24 ( June 2015), 16-19. DOI=10.5120/21408-4419

@article{ 10.5120/21408-4419,
author = { Yogita D. Shinde, Sudeep D. Thepade },
title = { Content based Image Retrieval using Sectorisation of Self Mutated Hybrid Wavelet Transforms },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 24 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 16-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number24/21408-4419/ },
doi = { 10.5120/21408-4419 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:07:05.284135+05:30
%A Yogita D. Shinde
%A Sudeep D. Thepade
%T Content based Image Retrieval using Sectorisation of Self Mutated Hybrid Wavelet Transforms
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 24
%P 16-19
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Content based image retrieval (CBIR) is an image retrieval process which involves mainly extraction of features based on contents of an image which uniquely identifies an image from other images in the database. Hybrid Wavelet Transform is formed using two orthogonal transforms. In this paper, Self Mutated Hybrid Wavelet transform (SMHWT) is used which is formed by using same component transform. In Proposed algorithm, feature extraction is done by applying sectorisation on Self Mutated Hybrid Wavelet transformed images. To test the performance of the proposed method, total 1000 queries were fired on the image database containing 1000 images of 10 categories. Manhattan Distance is used for similarity measurement. Performances proposed algorithm is evaluated using average precision. Results show that the proposed Self Mutated Hybrid Wavelet Transform containing Sine transform as a component gives better performance improvement across all tried variations of SMHWTs.

References
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  10. Sudeep D. Thepade, Yogita D. Shinde, "Robust CBIR using sectorisation of hybrid wavelet transforms with Cosine-Walsh, Cosine-Kekre, Cosine-Hartley combinations", International Conference on Pervasive Computing (ICPC), January 8-9, 2015, India.
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  12. http://wang. ist. psu. edu/docs/related/Image. orig.
Index Terms

Computer Science
Information Sciences

Keywords

CBIR Self Mutation Hybrid Wavelet Transform Sectorisation Manhattan Distance

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