An efficient and Automatic Algorithm for Image Forgery Detection
M.Srujana, Ch.Anuradha, Patnala S.R. Chandra Murty
Cite This Article:
An efficient and Automatic Algorithm for Image Forgery DetectionInternational Journal of Innovative Research in Technology( ,ISSN: 2349-6002 ,Volume 6 ,Issue 5 ,Page(s):192-196 ,October 2019 ,Available :IJIRT148715_PAPER.pdf
Forgery Detection, Adaptive Over-Segmentation, Local Color Feature, Forgery Region Extraction.
With the development of sophisticated image editing and manipulation tools, the originality and authenticity of a digital image is usually hard to determine visually. In order to detect digital image forgeries, various kinds of digital image forensics techniques have been proposed in the last decade. Compared with active forensics approaches that require embedding additional information, passive forensics approaches are more popular due to their wider application scenario, and have attracted increasing academic and industrial research interests. A novel copy-move forgery detection scheme using adaptive over-segmentation and feature point matching is proposed in this paper. The proposed scheme integrates both block-based and key point-based forgery detection methods. First, the proposed Adaptive Over-Segmentation algorithm segments the host image into non-overlapping and irregular blocks adaptively. Then, the feature points are extracted from each block as block features, and the block features are matched with one another to locate the labelled feature points; this procedure can approximately indicate the suspected forgery regions. To detect the forgery regions more accurately, we proposed, the Forgery Region Extraction algorithm, which replaces the feature points with small super pixels as feature blocks and then merges the neighbouring blocks that have similar local colour features into the feature blocks to generate the merged regions; finally, it applies the morphological operation to the merged regions to generate the detected forgery regions. The experimental results indicate that the proposed copy-move forgery detection scheme can achieve much better detection results even under various challenging conditions compared with the existing state-of-the-art copy-move forgery detection methods.
Article Details
Unique Paper ID: 148715

Publication Volume & Issue: Volume 6, Issue 5

Page(s): 192 - 196
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Last Date 25 January 2020

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