Image Forgery Detection with SIFT and RANSAC
Satish B Pratapur1, Shubhangi D.C2

1Satish B Pratapur, (Dept. of computer science & Engineering, VTU University, Belgavi-01
2Dr.Shubhangi D.C, (Head of the Dept. of Computer Science & Engineering, VTU University, Belgavi-01.

Manuscript received on 15 August 2019. | Revised Manuscript received on 25 August 2019. | Manuscript published on 30 September 2019. | PP: 1087-1092 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4245098319/19©BEIESP | DOI: 10.35940/ijrte.C4245.098319
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (

Abstract: In this paper, simulations were performed using SIFT and RANSAC to highlight the forged regions in the doctored image. SIFT algorithm is modified to consider unit vectors as the features of the blocks. Blocks with similar unit vectors were grouped into cluster. Mean values of the clusters were compared to determine the similarity between clusters. Once the clusters were formed, the image was subjected to RANSAC algorithm to determine the geometric transformation and to highlight the forged region in the doctored image. Two simulations were performed to test the performance of the proposed method. First, doctored image with only scaling and next, image with both scaling and rotation were tested. The simulation results are presented in detail.
Index Terms— Image forgery Detection, SIFT, RANSAC, Scaling, and Rotation.

Scope of the Article:
Image Processing and Pattern Recognition