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Article:Image Retrieval with Shape Features Extracted using Morphological Operators with BTC

by Sudeep Thepade, Priyadarshini Mukherjee, Miti Kakaiya, Shobhit Wadhwa, Satyajit Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 3
Year of Publication: 2010
Authors: Sudeep Thepade, Priyadarshini Mukherjee, Miti Kakaiya, Shobhit Wadhwa, Satyajit Singh
10.5120/1662-2238

Sudeep Thepade, Priyadarshini Mukherjee, Miti Kakaiya, Shobhit Wadhwa, Satyajit Singh . Article:Image Retrieval with Shape Features Extracted using Morphological Operators with BTC. International Journal of Computer Applications. 12, 3 ( December 2010), 1-5. DOI=10.5120/1662-2238

@article{ 10.5120/1662-2238,
author = { Sudeep Thepade, Priyadarshini Mukherjee, Miti Kakaiya, Shobhit Wadhwa, Satyajit Singh },
title = { Article:Image Retrieval with Shape Features Extracted using Morphological Operators with BTC },
journal = { International Journal of Computer Applications },
issue_date = { December 2010 },
volume = { 12 },
number = { 3 },
month = { December },
year = { 2010 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume12/number3/1662-2238/ },
doi = { 10.5120/1662-2238 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:00:42.023716+05:30
%A Sudeep Thepade
%A Priyadarshini Mukherjee
%A Miti Kakaiya
%A Shobhit Wadhwa
%A Satyajit Singh
%T Article:Image Retrieval with Shape Features Extracted using Morphological Operators with BTC
%J International Journal of Computer Applications
%@ 0975-8887
%V 12
%N 3
%P 1-5
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The paper discusses novel image retrieval methods based on edge texture of images extracted using morphological operators. The existing CBIR techniques are based on the feature vectors extracted from morphological edge extraction techniques such as simple morphological edge extraction technique, Top-Hat transform and Bottom-Hat transform. The proposed CBIR techniques are using the morphological edge extraction techniques with block truncation coding (BTC). The proposed techniques are tested on generic image database with 1000 images spread across 11 categories. In all 55 queries (5 from each category) are fired on the image database. The average precision and recall of all queries are computed and considered for performance analysis. The experimental results show that use of BTC over morphological shape images for feature extraction improves the performance of image retrieval with reduced computational complexity for query execution. In all BTC with simple morphological edge extraction based CBIR method (SMBTC) gives best performance.

References
  1. Dr.H.B.Kekre, Sudeep D. Thepade, Priyadarshini Mukherjee, Shobhit Wadhwa, Miti Kakaiya, Satyajit Singh, “Image Retrieval with Shape Features Extracted using Gradient Operators and Slope Magnitude Technique with BTC”, International Journal of Computer Applications, September 2010 issue.
  2. Dr.H.B.Kekre, Sudeep D. Thepade, “Rendering Futuristic Image Retrieval System”, National Conference on Enhancements in Computer, Communication and Information Technology, EC2IT-2009, 20-21 Mar 2009, K.J.Somaiya College of Engineering, Vidyavihar, Mumbai-77.
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Index Terms

Computer Science
Information Sciences

Keywords

CBIR Top-Hat Bottom-Hat BTC Morphology Edge extraction

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