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An Improvised Approach to Content based Image Retrieval

by K.Lakshmi Sudha, Megha Redkar, Anitha Ranganathan, Karishma Upadhyay
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 106 - Number 17
Year of Publication: 2014
Authors: K.Lakshmi Sudha, Megha Redkar, Anitha Ranganathan, Karishma Upadhyay
10.5120/18711-9688

K.Lakshmi Sudha, Megha Redkar, Anitha Ranganathan, Karishma Upadhyay . An Improvised Approach to Content based Image Retrieval. International Journal of Computer Applications. 106, 17 ( November 2014), 41-44. DOI=10.5120/18711-9688

@article{ 10.5120/18711-9688,
author = { K.Lakshmi Sudha, Megha Redkar, Anitha Ranganathan, Karishma Upadhyay },
title = { An Improvised Approach to Content based Image Retrieval },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 106 },
number = { 17 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 41-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume106/number17/18711-9688/ },
doi = { 10.5120/18711-9688 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:39:43.158447+05:30
%A K.Lakshmi Sudha
%A Megha Redkar
%A Anitha Ranganathan
%A Karishma Upadhyay
%T An Improvised Approach to Content based Image Retrieval
%J International Journal of Computer Applications
%@ 0975-8887
%V 106
%N 17
%P 41-44
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image matching is a fundamental aspect of many problems in computer vision, solving for 3D structure from multiple images, stereo correspondence, and motion tracking. An image may have features that have properties making them suitable for matching images. There have been various algorithms and optimizations for Content Based Image Retrieval. A few algorithms include Simple Harris, SIFT. Feature detectors and high matching consuming creates a low automation problem. To overcome these issues there have also been papers proposing optimized algorithms on Harris and SIFT [1]. This algorithm also has several flaws. The optimized algorithm uses Harris for feature extraction and description but Harris has a constraint that Harris detectors detect points only on black and white events. SIFT is flawed in itself since it is inefficient for poor resolution images and is also a time consuming algorithm [5]. The nearest neighbor search used as a matching algorithm is also time consuming and results in random overhead of outcomes. To overcome these shortcomings this paper proposes an algorithm that combines the advantages of Harris, SIFT and the matching algorithms. Color saliency is used along with Harris improvising its efficiency [6]. SIFT matching technique along with the nearest neighbor algorithm is supplemented with an epipolar concept to tender accurate results with lesser discrepant values.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Scale invariant features Epipolar constraint SIFT