CMF-iteMS: An automatic threshold selection for detection of copy-move forgery

Taking into consideration that the prior CMF detection methods rely on several fixed threshold values in the filtering process, we propose an efficient CMF detection method with an automatic threshold selection, named as CMF-iteMS. The CMF-iteMS recommends a PatchMatch-based CMF detection method tha...

Full description

Bibliographic Details
Main Authors:	Nor Bakiah, Abd. Warif, Mohd. Yamani Idna, Idris, Rosli, Salleh, Ahsiah, Ismail
Format:	Article
Language:	English
Published:	Elsevier Ltd. 2019
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/24414/ http://umpir.ump.edu.my/id/eprint/24414/ http://umpir.ump.edu.my/id/eprint/24414/ http://umpir.ump.edu.my/id/eprint/24414/1/CMF-iteMS-%20An%20automatic%20threshold%20selection%20for%20detection%20of%20copy-move%20forgery.pdf

id	ump-24414
recordtype	eprints
spelling	ump-244142019-03-20T01:32:52Z http://umpir.ump.edu.my/id/eprint/24414/ CMF-iteMS: An automatic threshold selection for detection of copy-move forgery Nor Bakiah, Abd. Warif Mohd. Yamani Idna, Idris Rosli, Salleh Ahsiah, Ismail QA76 Computer software Taking into consideration that the prior CMF detection methods rely on several fixed threshold values in the filtering process, we propose an efficient CMF detection method with an automatic threshold selection, named as CMF-iteMS. The CMF-iteMS recommends a PatchMatch-based CMF detection method that adapts Fourier-Mellin Transform (FMT) as the feature extraction technique while a new automatic threshold selection based on iterative means of regions size (iteMS) procedure is introduced to have flexibility in changing the threshold value for various characteristics (quality, sizes, and attacks) in each input image. To ensure the reliability of the proposed CMF-iteMS, the method is compared with four state-of-the-art CMF detection methods based on Scale Invariant Feature Transform (SIFT), patch matching, multi-scale analysis and symmetry techniques using three available datasets that cover the variety of characteristics in CMF images. The results show that the F-score of the CMF-iteMS outperformed existing CMF detection methods by exceeding an average of 90% F-score values for image-level evaluation and 82% of F-score value for pixel-level evaluation for all datasets in original size. As special attention is given to the image resizing attack, the method is able to maintain the highest performance even if the images in the datasets are resized to 0.25 parameter. Elsevier Ltd. 2019 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24414/1/CMF-iteMS-%20An%20automatic%20threshold%20selection%20for%20detection%20of%20copy-move%20forgery.pdf Nor Bakiah, Abd. Warif and Mohd. Yamani Idna, Idris and Rosli, Salleh and Ahsiah, Ismail (2019) CMF-iteMS: An automatic threshold selection for detection of copy-move forgery. Forensic Science International, 295. pp. 83-99. ISSN 0379-0738 https://doi.org/10.1016/j.forsciint.2018.12.004 https://doi.org/10.1016/j.forsciint.2018.12.004
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Nor Bakiah, Abd. Warif Mohd. Yamani Idna, Idris Rosli, Salleh Ahsiah, Ismail CMF-iteMS: An automatic threshold selection for detection of copy-move forgery
description	Taking into consideration that the prior CMF detection methods rely on several fixed threshold values in the filtering process, we propose an efficient CMF detection method with an automatic threshold selection, named as CMF-iteMS. The CMF-iteMS recommends a PatchMatch-based CMF detection method that adapts Fourier-Mellin Transform (FMT) as the feature extraction technique while a new automatic threshold selection based on iterative means of regions size (iteMS) procedure is introduced to have flexibility in changing the threshold value for various characteristics (quality, sizes, and attacks) in each input image. To ensure the reliability of the proposed CMF-iteMS, the method is compared with four state-of-the-art CMF detection methods based on Scale Invariant Feature Transform (SIFT), patch matching, multi-scale analysis and symmetry techniques using three available datasets that cover the variety of characteristics in CMF images. The results show that the F-score of the CMF-iteMS outperformed existing CMF detection methods by exceeding an average of 90% F-score values for image-level evaluation and 82% of F-score value for pixel-level evaluation for all datasets in original size. As special attention is given to the image resizing attack, the method is able to maintain the highest performance even if the images in the datasets are resized to 0.25 parameter.
format	Article
author	Nor Bakiah, Abd. Warif Mohd. Yamani Idna, Idris Rosli, Salleh Ahsiah, Ismail
author_facet	Nor Bakiah, Abd. Warif Mohd. Yamani Idna, Idris Rosli, Salleh Ahsiah, Ismail
author_sort	Nor Bakiah, Abd. Warif
title	CMF-iteMS: An automatic threshold selection for detection of copy-move forgery
title_short	CMF-iteMS: An automatic threshold selection for detection of copy-move forgery
title_full	CMF-iteMS: An automatic threshold selection for detection of copy-move forgery
title_fullStr	CMF-iteMS: An automatic threshold selection for detection of copy-move forgery
title_full_unstemmed	CMF-iteMS: An automatic threshold selection for detection of copy-move forgery
title_sort	cmf-items: an automatic threshold selection for detection of copy-move forgery
publisher	Elsevier Ltd.
publishDate	2019
url	http://umpir.ump.edu.my/id/eprint/24414/ http://umpir.ump.edu.my/id/eprint/24414/ http://umpir.ump.edu.my/id/eprint/24414/ http://umpir.ump.edu.my/id/eprint/24414/1/CMF-iteMS-%20An%20automatic%20threshold%20selection%20for%20detection%20of%20copy-move%20forgery.pdf
first_indexed	2023-09-18T22:36:56Z
last_indexed	2023-09-18T22:36:56Z
_version_	1777416657901191168

CMF-iteMS: An automatic threshold selection for detection of copy-move forgery

Similar Items