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A Novel Approach for Detection of Copy-Move Forgery

Authors:
Mengyu Qiao
Andrew Sung
Qingzhong Liu
Bernardete Ribeiro

Keywords: Copy-Move Forgery; Image Forensics; Curvelet Transform

Abstract:
With the increasing popularity of digital media and the ubiquitous availability of media editing software, innocuous multimedia are easily tampered for malicious purposes. Copy-move forgery is one important category of image forgery, in which a part of an image is duplicated, and substitutes another part of the same image at a different location. Therefore, it is necessary to have reliable and efficient methods to detect copy-move forgery for applications in law enforcement, forensics, etc. In this paper, based on multi-resolution and multi-orientation curvelet transform, we propose a blind forensics approach for the detection of copy-move forgery. In detail, the input image is segmented into overlapping blocks, and then curvelet transform is applied to each block. Statistics of curvelet sub-bands are extracted and sorted. Finally, duplicated blocks are identified by comparing their similarity. The proposed approach intends to reduce the complexity, improve the accuracy of the detection, and potentially resist shifting manipulation.

Pages: 44 to 47

Copyright: Copyright (c) IARIA, 2011

Publication date: November 20, 2011

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-172-4

Location: Lisbon, Portugal

Dates: from November 20, 2011 to November 25, 2011