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Digital image forgery detection using JPEG features and local noise discrepancies
Liu B.; Pun C.-M.; Yuan X.-C.
2014-03-16
Source PublicationThe Scientific World Journal
ISSN1537744X
Volume2014
Abstract

Wide availability of image processing software makes counterfeiting become an easy and low-cost way to distort or conceal facts. Driven by great needs for valid forensic technique, many methods have been proposed to expose such forgeries. In this paper, we proposed an integrated algorithm which was able to detect two commonly used fraud practices: copy-move and splicing forgery in digital picture. To achieve this target, a special descriptor for each block was created combining the feature from JPEG block artificial grid with that from noise estimation. And forehand image quality assessment procedure reconciled these different features by setting proper weights. Experimental results showed that, compared to existing algorithms, our proposed method is effective on detecting both copy-move and splicing forgery regardless of JPEG compression ratio of the input image. © 2014 Bo Liu et al.

DOI10.1155/2014/230425
URLView the original
Indexed BySCI
Language英语
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000333600500001
PublisherHINDAWI PUBLISHING CORPORATION
The Source to ArticleScopus
Fulltext Access
Citation statistics
Cited Times [WOS]:4   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorPun C.-M.
AffiliationDepartment of Computer and Information Science, University of Macau, Macau, China
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Liu B.,Pun C.-M.,Yuan X.-C.. Digital image forgery detection using JPEG features and local noise discrepancies[J]. The Scientific World Journal,2014,2014.
APA Liu B.,Pun C.-M.,&Yuan X.-C..(2014).Digital image forgery detection using JPEG features and local noise discrepancies.The Scientific World Journal,2014.
MLA Liu B.,et al."Digital image forgery detection using JPEG features and local noise discrepancies".The Scientific World Journal 2014(2014).
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