![](/images/graphics-bg.png)
Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies
Joint Authors
Liu, Bo
Pun, Chi-Man
Yuan, Xiao-Chen
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-16
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Liu, Bo& Pun, Chi-Man& Yuan, Xiao-Chen. 2014. Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1048801
Modern Language Association (MLA)
Liu, Bo…[et al.]. Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies. The Scientific World Journal No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1048801
American Medical Association (AMA)
Liu, Bo& Pun, Chi-Man& Yuan, Xiao-Chen. Digital Image Forgery Detection Using JPEG Features and Local Noise Discrepancies. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1048801
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048801