Geometric transformations parameters estimation from copy-move forgery using image blobs and keypoints

dc.contributor.author Patrick, Niyishaka
dc.contributor.author Bhagvati, Chakravarthy
dc.date.accessioned 2022-03-27T05:54:15Z
dc.date.available 2022-03-27T05:54:15Z
dc.date.issued 2022-01-01
dc.description.abstract A copy-move forgery is a passive tampering wherein one or more regions have been copied and pasted within the same image. Often, geometric transformations, including scale, rotation, and rotation+scale are applied to the forged areas to conceal the counterfeits to the copy-move forgery detection methods. Recently, copy-move forgery detection using image blobs have been used to tackle the limitation of the existing detection methods. However, the main limitation of blobs-based copy-move forgery detection methods is the inability to perform the geometric transformation estimation. To tackle the above-mentioned limitation, this article presents a technique that detects copy-move forgery and estimates the geometric transformation parameters between the authentic region and its duplicate using image blobs and scale-rotation invariant keypoints. The proposed algorithm involves the following steps: image blobs are found in the image being analyzed; scale-rotation invariant features are extracted; the keypoints that are located within the same blob are identified; feature matching is performed between keypoints that are located within different blobs to find similar features; finally, the blobs with matched keypoints are post-processed and a 2D affine transformations is computed to estimate the geometric transformation parameters. Our technique is flexible and can easily take in various scale-rotation invariant keypoints including AKAZE, ORB, BRISK, SURF, and SIFT to enhance the effectiveness. The proposed algorithm is implemented and evaluated on images forged with copy-move regions combined with geometric transformation from standard datasets. The experimental results indicate that the new algorithm is effective for geometric transformation parameters estimation.
dc.identifier.citation Multimedia Tools and Applications. v.81(2)
dc.identifier.issn 13807501
dc.identifier.uri 10.1007/s11042-021-11642-0
dc.identifier.uri https://link.springer.com/10.1007/s11042-021-11642-0
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/8699
dc.subject 2D Affine transformation
dc.subject Blobs
dc.subject CMF
dc.subject CMFD
dc.subject DoG
dc.title Geometric transformations parameters estimation from copy-move forgery using image blobs and keypoints
dc.type Journal. Article
dspace.entity.type
Files
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Plain Text
Description: