Novel Copy Move Forgery Detection Based on Repeated Feature Extraction and Delaunay Triangulation
Dhanya R1, Kalaiselvi R2
1Dhanya R*, Research Scholar, Department of Computer Applications, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu, India.
2Kalaiselvi R, Associate Professor, Department of Computer Science & Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu, India.
Manuscript received on December 14, 2019. | Revised Manuscript received on December 21, 2019. | Manuscript published on January 10, 2020. | PP: 2364-2369 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8971019320/2020©BEIESP | DOI: 10.35940/ijitee.C8971.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Nowadays new and creative methods of forging images are developed with the invention of sophisticated softwares like Adobe photoshop. Tools available in such softwares will make the forged image look real which cannot be even identified by a naked eye. In this paper, key point based approach of taking out features using Scale Invariant Feature Transform (SIFT) is used. The feature points thus extracted are then modeled to get a set of triangles using Delaunay Triangulation method. These triangles are matched using mean vertex descriptor and the removal of false positives is done using the method of Random Sample Consensus (RANSAC). Implementation show that the proposed approach outdoes the equivalent methods
Keywords: Forensic Image Processing, Forgery detection, Delaunay Triangulation, Copy-Move Forgery.
Scope of the Article: Signal and Image Processing