Detection of Video and Multimedia Copy-Move Forgery using Optical Algorithm and GLSM Clustering
Seemanthini. K1, Manjunath S S2, Raghuram A S3, Sneha N P4

1Prof. Seemanthini. K, Assistant Professor, Department of ISE, Dayananda Sagar Academy of Technology and Management, Bangalore (Karnataka), India.

2Dr. Manjunath S S, HOD, Department of CSE, ATME College of Enginering, Mysore (Karnataka), India.

3Raghuram A S, Assistant Professor, Department of CSE, ATME College of Enginering, Mysore (Karnataka), India.

4Sneha N P, Assistant Professor, Department of CSE, ATME College of Enginering, Mysore (Karnataka), India.

Manuscript received on 04 December 2019 | Revised Manuscript received on 12 December 2019 | Manuscript Published on 31 December 2019 | PP: 200-205 | Volume-9 Issue-2S December 2019 | Retrieval Number: B14191292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1419.1292S19

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Abstract: Digital Videos and multimedia copy-move forgery detection is a trending topic in multimedia forensics. Protecting videos and other digital media from tampering has become a cause of concern. Video copy-move forgery has increasingly become a type of cybercrime that is employed to using videos for various malicious purposes such as providing fake evidences in court rooms, spreading fake rumors, using it to defame a person. A lot of approaches have been proposed for detecting the traces left by any forgery caused due to the copy-move operation. In this paper, we conduct a survey on these existing approaches which are applied for the detection of copy –move videos and also for the identification forgery in the images. In some of the existing methods, the problem of copy-move video forgery has been addressed using different techniques. Techniques such as noise residue, motion and brightness gradients, optical flow techniques solve only part of the whole problem. This survey analyses the current solutions and what they offer to address this problem.

Keywords: Noise Residue, Copy-move Forgery, Optical Flow, Copy- Move Forgery, Motion Brightness.
Scope of the Article: Clustering