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Reseach Article

Development of an Improved Feature Based Algorithm for Image Matching

by Kanwalvir Singh Dhindsa, Geetanjali Babbar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 14 - Number 8
Year of Publication: 2011
Authors: Kanwalvir Singh Dhindsa, Geetanjali Babbar
10.5120/1903-2537

Kanwalvir Singh Dhindsa, Geetanjali Babbar . Development of an Improved Feature Based Algorithm for Image Matching. International Journal of Computer Applications. 14, 8 ( February 2011), 23-26. DOI=10.5120/1903-2537

@article{ 10.5120/1903-2537,
author = { Kanwalvir Singh Dhindsa, Geetanjali Babbar },
title = { Development of an Improved Feature Based Algorithm for Image Matching },
journal = { International Journal of Computer Applications },
issue_date = { February 2011 },
volume = { 14 },
number = { 8 },
month = { February },
year = { 2011 },
issn = { 0975-8887 },
pages = { 23-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume14/number8/1903-2537/ },
doi = { 10.5120/1903-2537 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:02:51.771960+05:30
%A Kanwalvir Singh Dhindsa
%A Geetanjali Babbar
%T Development of an Improved Feature Based Algorithm for Image Matching
%J International Journal of Computer Applications
%@ 0975-8887
%V 14
%N 8
%P 23-26
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image matching plays an important role in many fields such as pattern searching & recognizing[6], image analysis, robotics & computer vision. It is a method to find a certain image in the image database which matches or can be said similar to the given template picture. The template image can be thought of as a subset of the matching image. This paper aims at the improved matching algorithm which is based on the image feature point[5]. By searching correct feature point and setting bidirectional threshold value, the matching process can be quickly & precisely implemented with optimistic results. Visual C++ to be used for design and implementation. In future, the feature based algorithm can be modified to choose feature selection threshold adaptively depending on the image’s content.

References
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Index Terms

Computer Science
Information Sciences

Keywords

correspondence image features convergence versatility