Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162782
Title: Copy-move image forgery detection based on evolving circular domains coverage
Authors: Lu, Shilin
Hu, Xinghong
Wang, Chengyou
Chen, Lu
Han, Shulu
Han, Yuejia
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Source: Lu, S., Hu, X., Wang, C., Chen, L., Han, S. & Han, Y. (2022). Copy-move image forgery detection based on evolving circular domains coverage. Multimedia Tools and Applications, 81(26), 37847-37872. https://dx.doi.org/10.1007/s11042-022-12755-w
Journal: Multimedia Tools and Applications
Abstract: The aim of this paper is to improve the accuracy of copy-move forgery detection (CMFD) in image forensics by proposing a novel scheme and the main contribution is evolving circular domains coverage (ECDC) algorithm. The proposed scheme integrates both block-based and keypoint-based forgery detection methods. Firstly, the speed-up robust feature (SURF) in log-polar space and the scale invariant feature transform (SIFT) are extracted from an entire image. Secondly, generalized 2 nearest neighbor (g2NN) is employed to get massive matched pairs. Then, random sample consensus (RANSAC) algorithm is employed to filter out mismatched pairs, thus allowing rough localization of counterfeit areas. To present these forgery areas more accurately, we propose the efficient and accurate ECDC algorithm to present them. This algorithm can find satisfactory threshold areas by extracting block features from jointly evolving circular domains, which are centered on matched pairs. Finally, morphological operation is applied to refine the detected forgery areas. Experimental results indicate that the proposed CMFD scheme can achieve better detection performance under various attacks compared with other state-of-the-art CMFD schemes.
URI: https://hdl.handle.net/10356/162782
ISSN: 1380-7501
DOI: 10.1007/s11042-022-12755-w
Rights: © The Author(s) 2022. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Fulltext Permission: open
Fulltext Availability: With Fulltext
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