Coarse-to-fine copy-move image forgery detection method based on discrete cosine transform

Digital image forgery has become a serious problem in the present society. As the world is advancing in the information and communication technology, it has become more crucial for researchers to take part in overcoming the wide-spreading digital image forgery to prove an image authenticity especial...

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Main Author:	Mohd. Azol, Mas Elyna
Format:	Thesis
Language:	English
Published:	2016
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/78797/1/MasElynaMohdMFC2016.pdf
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spelling	my-utm-ep.787972018-09-17T04:12:56Z Coarse-to-fine copy-move image forgery detection method based on discrete cosine transform 2016-08 Mohd. Azol, Mas Elyna QA75 Electronic computers. Computer science Digital image forgery has become a serious problem in the present society. As the world is advancing in the information and communication technology, it has become more crucial for researchers to take part in overcoming the wide-spreading digital image forgery to prove an image authenticity especially when the legislative field is involved. Copy-move forgery is a type of image forgery where one part of an image is copied and pasted in other regions of the same image, and it is one of the most common image forgeries to conceal some information in the original image. There are numerous techniques available to detect copy-move forgeries which each of them have their own advantages and drawbacks. Discrete Cosine Transform (DCT) is a powerful algorithm developed as a method to detect copy-move forgery which is well known for its detection efficiency. However, the detection rate relies intensely on the size of block used. Small block size is known for its ability to detect fine cloned objects, but the drawback is it produces too many false positive and requires high execution time. In this research, a method to overcome the weaknesses of using small block size by applying the coarse-to-fine approach with the two-tier process is proposed. The proposed method is evaluated on fifteen forged images on the CoMoFoD dataset. The results demonstrated that the proposed method is able to achieve high precision and recall rate of over 90% as well as improves the computation time by reducing the overall duration of forgery detection up to 73% compared to the traditional DCT method using small block size. Therefore, these findings validate that the proposed method offers a trade-off between accuracy and runtime. 2016-08 Thesis http://eprints.utm.my/id/eprint/78797/ http://eprints.utm.my/id/eprint/78797/1/MasElynaMohdMFC2016.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:109821 masters Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Mohd. Azol, Mas Elyna Coarse-to-fine copy-move image forgery detection method based on discrete cosine transform
description	Digital image forgery has become a serious problem in the present society. As the world is advancing in the information and communication technology, it has become more crucial for researchers to take part in overcoming the wide-spreading digital image forgery to prove an image authenticity especially when the legislative field is involved. Copy-move forgery is a type of image forgery where one part of an image is copied and pasted in other regions of the same image, and it is one of the most common image forgeries to conceal some information in the original image. There are numerous techniques available to detect copy-move forgeries which each of them have their own advantages and drawbacks. Discrete Cosine Transform (DCT) is a powerful algorithm developed as a method to detect copy-move forgery which is well known for its detection efficiency. However, the detection rate relies intensely on the size of block used. Small block size is known for its ability to detect fine cloned objects, but the drawback is it produces too many false positive and requires high execution time. In this research, a method to overcome the weaknesses of using small block size by applying the coarse-to-fine approach with the two-tier process is proposed. The proposed method is evaluated on fifteen forged images on the CoMoFoD dataset. The results demonstrated that the proposed method is able to achieve high precision and recall rate of over 90% as well as improves the computation time by reducing the overall duration of forgery detection up to 73% compared to the traditional DCT method using small block size. Therefore, these findings validate that the proposed method offers a trade-off between accuracy and runtime.
format	Thesis
qualification_level	Master's degree
author	Mohd. Azol, Mas Elyna
author_facet	Mohd. Azol, Mas Elyna
author_sort	Mohd. Azol, Mas Elyna
title	Coarse-to-fine copy-move image forgery detection method based on discrete cosine transform
title_short	Coarse-to-fine copy-move image forgery detection method based on discrete cosine transform
title_full	Coarse-to-fine copy-move image forgery detection method based on discrete cosine transform
title_fullStr	Coarse-to-fine copy-move image forgery detection method based on discrete cosine transform
title_full_unstemmed	Coarse-to-fine copy-move image forgery detection method based on discrete cosine transform
title_sort	coarse-to-fine copy-move image forgery detection method based on discrete cosine transform
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2016
url	http://eprints.utm.my/id/eprint/78797/1/MasElynaMohdMFC2016.pdf
_version_	1747818073651412992

Coarse-to-fine copy-move image forgery detection method based on discrete cosine transform

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