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 2022 Vol.14(2): 79-83 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2022.V14.1313

A Novel Copy-Move Forgery Detection Using Combined ORB-PCA Approach

Krishna H. Hingrajiya and Ravi K. Sheth

Abstract—The integration of digital images in various forms is become essential in daily life. At the same time, it presents the serious concern about the authenticity of these images when they are used to convey important information. It became very easy to modify the information presented in an image with the availability of different editing tools and techniques. And hence the detection of forged image is much needed with efficient image forgery detection technique. In current work, an effective approach combining Principal Component Analysis and Oriented FAST and Rotated BRIEF is used to detect copy move forgery. Principle Component Analysis (PCA) is used to reduce the dimension of the features and then Oriented FAST and Rotated BRIEF (ORB) is applied to extract the key points. The results showcased the ability of presented approach in form of robustness in feature extraction and matching the key points with less computation time compared to SIFT and SURF.

Index Terms—Image forgery detection, copy-move, image splicing, PCA, ORB.

Krishna H. Hingrajiya is with School of IT, Artificial Intelligence and Cyber Security, Rashtriya Raksha University, India, and Computer Engineering Department, Gandhinagar Institute of Technology, India (e-mail: krishna.hingrajiya@git.org.in). Ravi K. Sheth is with School of IT, Artificial Intelligence and Cyber Security, Rashtriya Raksha University, India (e-mail: ravi.sheth@rru.ac.in).

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Cite:Krishna H. Hingrajiya and Ravi K. Sheth, "A Novel Copy-Move Forgery Detection Using Combined ORB-PCA Approach," International Journal of Computer Theory and Engineering vol. 14, no. 2, pp. 79-83, 2022.

Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).


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