Exposing digital image forgeries by detecting discrepancies in motion blur

The widespread availability of photo manipulation software has made it unprecedentedly easy to manipulate images for malicious purposes. Image splicing is one such form of tampering. In recent years, researchers have proposed various methods for detecting such splicing. In this paper, we present a n...

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Main Authors: Kakar, Pravin, Ser, Wee, Sudha, N.
Other Authors: Institute for Media Innovation
Format: Article
Language:English
Published: 2012
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Online Access:https://hdl.handle.net/10356/94946
http://hdl.handle.net/10220/8586
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-949462020-09-26T21:54:24Z Exposing digital image forgeries by detecting discrepancies in motion blur Kakar, Pravin Ser, Wee Sudha, N. Institute for Media Innovation DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision The widespread availability of photo manipulation software has made it unprecedentedly easy to manipulate images for malicious purposes. Image splicing is one such form of tampering. In recent years, researchers have proposed various methods for detecting such splicing. In this paper, we present a novel method of detecting splicing in images, using discrepancies in motion blur. We use motion blur estimation through image gradients in order to detect inconsistencies between the spliced region and the rest of the image. We also develop a new measure to assist in inconsistent region segmentation in images that contain small amounts of motion blur. Experimental results show that our technique provides good segmentation of regions with inconsistent motion blur. We also provide quantitative comparisons with other existing blur-based techniques over a database of images. It is seen that our technique gives significantly better detection results. Accepted version 2012-09-20T02:46:50Z 2019-12-06T19:05:10Z 2012-09-20T02:46:50Z 2019-12-06T19:05:10Z 2011 2011 Journal Article Kakar, P., Sudha, N., & Ser, W. (2011). Exposing digital image forgeries by detecting discrepancies in motion blur. IEEE Transactions On Multimedia, 13 (3), 443-452. https://hdl.handle.net/10356/94946 http://hdl.handle.net/10220/8586 10.1109/TMM.2011.2121056 en IEEE transactions on multimedia © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [DOI: http://dx.doi.org/10.1109/TMM.2011.2121056]. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Kakar, Pravin
Ser, Wee
Sudha, N.
Exposing digital image forgeries by detecting discrepancies in motion blur
description The widespread availability of photo manipulation software has made it unprecedentedly easy to manipulate images for malicious purposes. Image splicing is one such form of tampering. In recent years, researchers have proposed various methods for detecting such splicing. In this paper, we present a novel method of detecting splicing in images, using discrepancies in motion blur. We use motion blur estimation through image gradients in order to detect inconsistencies between the spliced region and the rest of the image. We also develop a new measure to assist in inconsistent region segmentation in images that contain small amounts of motion blur. Experimental results show that our technique provides good segmentation of regions with inconsistent motion blur. We also provide quantitative comparisons with other existing blur-based techniques over a database of images. It is seen that our technique gives significantly better detection results.
author2 Institute for Media Innovation
author_facet Institute for Media Innovation
Kakar, Pravin
Ser, Wee
Sudha, N.
format Article
author Kakar, Pravin
Ser, Wee
Sudha, N.
author_sort Kakar, Pravin
title Exposing digital image forgeries by detecting discrepancies in motion blur
title_short Exposing digital image forgeries by detecting discrepancies in motion blur
title_full Exposing digital image forgeries by detecting discrepancies in motion blur
title_fullStr Exposing digital image forgeries by detecting discrepancies in motion blur
title_full_unstemmed Exposing digital image forgeries by detecting discrepancies in motion blur
title_sort exposing digital image forgeries by detecting discrepancies in motion blur
publishDate 2012
url https://hdl.handle.net/10356/94946
http://hdl.handle.net/10220/8586
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