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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
  1. R. C. Joshi, and Shashikala Tapaswi, “Image Similarity: A Genetic Algorithm Based Approach”, Proceedings of world academy of science, engineering and technology volume 21 MAY 2007 ISSN 1307-6884
  2. Hu Minghao, Ren Mingwu, Yang Jingyu, “ A rapid and useful algorithm of image matching based on Feature Point”, computer engineering 2004.5 Vol.30
  3. Li Junshan, Shen Xubang,”the research of image matching technology”, Micro-electric and computer 2002-2
  4. Abdul Ghafoor, Rao Naveed Iqbal, and Shoab Khan, ”Robust image matching algorithm”, EC-VIP-MC 2003,4th EURASIP Conference focused on Video/Image Processing and Multimedia Communications, 2-5 July 2003, Zagreb, Croatia.
  5. Dare P M, Dow man, “A Comparison of feature extraction algorithms for automated feature based multisensor image registration”, IJRSS'97, 1997
  6. Gu Hui, Chen Guangyi and Cao Wenming, “Image Matching Algorithm Based on Feature Point with Bidrectional Threshold”, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310031, Zhenjiang, China, 2005 IEEE.
  7. Hassan Hajjdiab and Robert Laganiere, ”Complexity Analysis of Feature- Based Image Matching”, World Academy of Science, Engineering and Technology 51, 2009.
  8. Ida JAZAYERI, Simon CRONK and Clive FRASER, ”A Feature Based Matching Approach to Automated Object Reconstruction in Multi-Image Close-Range Photogrammetry”, FIG Congress, Facing the Challenges – Building the Capacity, Sydney, Australia, 11-16 April 2010.
  9. Weili JIAO, Yaling FANG, Guojin, “An Integrated Feature Based Method for sub-pixel Image matching”, the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B1. , Beijing 100086, CHINA, 2008.
  10. Jazayeri, I., Fraser, “Interest Operators for Feature-Based Matching in Close-Range Photogrammetry”. Photogrammetric Record (in press) C.S. (2009).
Index Terms

Computer Science
Information Sciences

Keywords

correspondence image features convergence versatility