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Proceedings Paper

Thinking beyond the block: block matching for copy-move forgery detection revisited
Author(s): Matthias Kirchner; Pascal Schoettle; Christian Riess
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Paper Abstract

Detection of copy{move forgeries is one of the most actively researched topics in image forensics. It has been shown that so-called block-based methods give the highest pixel-wise accuracy for detecting copy{move forgeries. However, matching of block-based features can be computationally extremely demanding. Hence, the current predominant line of thought is that block-based algorithms are too slow to be applicable in practice. In this paper, we revisit the matching stage of block-based copy{move forgery detection methods. We propose an efficient approach for finding duplicate patterns of a given size in integer-valued input data. By design, we focus on the spatial relation of potentially duplicated elements. This allows us to locate copy{move forgeries via bit-wise operations, without expensive block comparisons in the feature space. Experimental investigation of different matching strategies shows that the proposed method has its benefits. However, on a broader scale, our experiments demonstrate that the performance of matching by lexicographic sorting might have been underestimated in previous work, despite its remarkable speed benefit on large images. In fact, in a practical setting, where accuracy and computational efficiency have to be balanced, lexicographic sorting may be considered the method of choice.

Paper Details

Date Published: 4 March 2015
PDF: 12 pages
Proc. SPIE 9409, Media Watermarking, Security, and Forensics 2015, 940903 (4 March 2015); doi: 10.1117/12.2082789
Show Author Affiliations
Matthias Kirchner, Binghamton Univ. (United States)
Pascal Schoettle, Westfälische Wilhelms-Univ. Münster (Germany)
Christian Riess, Stanford School of Medicine (United States)

Published in SPIE Proceedings Vol. 9409:
Media Watermarking, Security, and Forensics 2015
Adnan M. Alattar; Nasir D. Memon; Chad D. Heitzenrater, Editor(s)

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