Understanding if a digital image is authentic or not, is a key purpose of image forensics. There are several different tampering attacks but, surely, one of the most common and immediate one is copy-move. A recent and effective approach for detecting copy-move forgeries is to use local visual features such as SIFT. In this kind of methods, SIFT matching is often followed by a clustering procedure to group keypoints that are spatially close. Often, this procedure could be unsatisfactory, in particular in those cases in which the copied patch contains pixels that are spatially very distant among them, and when the pasted area is near to the original source. In such cases, a better estimation of the cloned area is necessary in order to obtain an accurate forgery localization. In this paper a novel approach is presented for copy-move forgery detection and localization based on the J-Linkage algorithm, which performs a robust clustering in the space of the geometric transformation. Experimental results, carried out on different datasets, show that the proposed method outperforms other similar state-of-the-art techniques both in terms of copy-move forgery detection reliability and of precision in the manipulated patch localization.
Copy-move forgery detection and localization by means of robust clustering with J-Linkage / Amerini, Irene; Ballan, Lamberto; Caldelli, Roberto; DEL BIMBO, Alberto; Del Tongo, Luca; Serra, Giuseppe. - In: SIGNAL PROCESSING-IMAGE COMMUNICATION. - ISSN 0923-5965. - 28:6(2013), pp. 659-669. [10.1016/j.image.2013.03.006]
Copy-move forgery detection and localization by means of robust clustering with J-Linkage
Irene Amerini
;Alberto Del Bimbo
;
2013
Abstract
Understanding if a digital image is authentic or not, is a key purpose of image forensics. There are several different tampering attacks but, surely, one of the most common and immediate one is copy-move. A recent and effective approach for detecting copy-move forgeries is to use local visual features such as SIFT. In this kind of methods, SIFT matching is often followed by a clustering procedure to group keypoints that are spatially close. Often, this procedure could be unsatisfactory, in particular in those cases in which the copied patch contains pixels that are spatially very distant among them, and when the pasted area is near to the original source. In such cases, a better estimation of the cloned area is necessary in order to obtain an accurate forgery localization. In this paper a novel approach is presented for copy-move forgery detection and localization based on the J-Linkage algorithm, which performs a robust clustering in the space of the geometric transformation. Experimental results, carried out on different datasets, show that the proposed method outperforms other similar state-of-the-art techniques both in terms of copy-move forgery detection reliability and of precision in the manipulated patch localization.File | Dimensione | Formato | |
---|---|---|---|
Amerini_Copy-move_2013.pdf
solo gestori archivio
Tipologia:
Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
4.02 MB
Formato
Adobe PDF
|
4.02 MB | Adobe PDF | Contatta l'autore |
VE_2013_11573-1324983.pdf
solo gestori archivio
Tipologia:
Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
4.02 MB
Formato
Adobe PDF
|
4.02 MB | Adobe PDF | Contatta l'autore |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.