General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail: ijcte@iacsitp.com
    • Journal Metrics:

Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2014 Vol.6(5): 407-411 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2014.V6.899

A Featured Area-Based Image Registration

Youngsung Soh, Mudasar Qadir, Aamer Mehmood, Yongsuk Hae, Hadi Ashraf, and Intaek Kim

Abstract—Image registration is necessary when images from multiple viewpoints need be brought into common coordinate system. Image registration techniques can be classified as area-based methods and feature-based methods. In area-based methods, no features are selected and regularly tessellated areas are usually used for matching. In feature-based methods, features such as regions, lines, and prominent points are detected and used for matching. When image contains rich features, feature-based methods are preferred and when it does not, area-based methods are usually adopted. There are occasions where richness of features varies locally in the image. In this case, either area-based methods or feature-based methods alone may not generate successful results. In this paper, we propose a mixture of two methods termed as featured area-based method. In the proposed, we first tessellate the image into equal-sized areas, estimate richness of features of each area utilizing the edge direction histogram, choose only those areas with a certain level of richness, and use them for matching. We compared the proposed with well-known conventional methods such as Kanade-Lucas-Tomasi(KLT) method, speeded up robust features (SURF), and scale-invariant feature transform (SIFT), and showed that the proposed performs better than others.

Index Terms—Image registration, KLT, SIFT, SURF.

The authors are with the Myongji University, Yongin, 449-728, Korea (e-mail: soh@mju.ac.kr, mudasar.kalwar@gmail.com, aamergcu@hotmail.com; wise_sunys@nate.com, nothan111@gmail.com, kit@mju.ac.kr).

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Cite:Youngsung Soh, Mudasar Qadir, Aamer Mehmood, Yongsuk Hae, Hadi Ashraf, and Intaek Kim, "A Featured Area-Based Image Registration," International Journal of Computer Theory and Engineering vol. 6, no. 5, pp. 407-411, 2014.


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