Enhanced dominated completed median ternary pattern for detection of copy-move image forgery against post-processing operations

Copy-move forgery which is an act of copying an object and pasting it on another location of the same image is one of the most common types of tampering techniques to manipulate image content. Besides, most of the images are also being tampered by post-processing operations such as JPEG compression,...

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Main Author:	Muhamad, Rafidah
Format:	Thesis
Language:	English
Published:	2020
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/96437/1/RafidahMuhammadMFABU2020.pdf.pdf
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id	my-utm-ep.96437
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spelling	my-utm-ep.964372022-07-24T09:56:19Z Enhanced dominated completed median ternary pattern for detection of copy-move image forgery against post-processing operations 2020 Muhamad, Rafidah QA75 Electronic computers. Computer science Copy-move forgery which is an act of copying an object and pasting it on another location of the same image is one of the most common types of tampering techniques to manipulate image content. Besides, most of the images are also being tampered by post-processing operations such as JPEG compression, contrast adjustment, brightness change, colour reduction, noise addition, and blurring before pasted, makes it more challenging to detect, as found in the standard dataset CoMoFoD. In multimedia forensics, many efforts have been undertaken to detect whether an image is pristine or manipulated by proposing various techniques to improve the robustness of these detection methods. However, researchers continue to face challenges in detecting tampered region with the presence of all these post-processing attacks in a copy-move image forgery and relatively few methods were attempted to address them. The main objective of this research is to design and develop an improved descriptor with features invariance to post-processing operations for copy-move forgery detection. Generally, image processing steps consist of four main steps which are pre-processing, feature extraction, block matching and evaluation of results. In this process, an improvement is made by employing sign operator for feature extraction with mean (robust) as threshold to extract invariance feature vectors against post-processing attacks from each block of image. An Euclidean distance is employed to filter out the weak features and obtain rough suspected matches. The results obtained were very encouraging with Correct Detection Rate (CDR) of more than 99% achieved for the normal tampered images, while the ones with post-processing operations fluctuated between 91% and 99.7%. The results have proven that the proposed copy-move forgery detection performed better than the existing techniques. 2020 Thesis http://eprints.utm.my/id/eprint/96437/ http://eprints.utm.my/id/eprint/96437/1/RafidahMuhammadMFABU2020.pdf.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:142165 masters Universiti Teknologi Malaysia Faculty of Engineering - School of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Muhamad, Rafidah Enhanced dominated completed median ternary pattern for detection of copy-move image forgery against post-processing operations
description	Copy-move forgery which is an act of copying an object and pasting it on another location of the same image is one of the most common types of tampering techniques to manipulate image content. Besides, most of the images are also being tampered by post-processing operations such as JPEG compression, contrast adjustment, brightness change, colour reduction, noise addition, and blurring before pasted, makes it more challenging to detect, as found in the standard dataset CoMoFoD. In multimedia forensics, many efforts have been undertaken to detect whether an image is pristine or manipulated by proposing various techniques to improve the robustness of these detection methods. However, researchers continue to face challenges in detecting tampered region with the presence of all these post-processing attacks in a copy-move image forgery and relatively few methods were attempted to address them. The main objective of this research is to design and develop an improved descriptor with features invariance to post-processing operations for copy-move forgery detection. Generally, image processing steps consist of four main steps which are pre-processing, feature extraction, block matching and evaluation of results. In this process, an improvement is made by employing sign operator for feature extraction with mean (robust) as threshold to extract invariance feature vectors against post-processing attacks from each block of image. An Euclidean distance is employed to filter out the weak features and obtain rough suspected matches. The results obtained were very encouraging with Correct Detection Rate (CDR) of more than 99% achieved for the normal tampered images, while the ones with post-processing operations fluctuated between 91% and 99.7%. The results have proven that the proposed copy-move forgery detection performed better than the existing techniques.
format	Thesis
qualification_level	Master's degree
author	Muhamad, Rafidah
author_facet	Muhamad, Rafidah
author_sort	Muhamad, Rafidah
title	Enhanced dominated completed median ternary pattern for detection of copy-move image forgery against post-processing operations
title_short	Enhanced dominated completed median ternary pattern for detection of copy-move image forgery against post-processing operations
title_full	Enhanced dominated completed median ternary pattern for detection of copy-move image forgery against post-processing operations
title_fullStr	Enhanced dominated completed median ternary pattern for detection of copy-move image forgery against post-processing operations
title_full_unstemmed	Enhanced dominated completed median ternary pattern for detection of copy-move image forgery against post-processing operations
title_sort	enhanced dominated completed median ternary pattern for detection of copy-move image forgery against post-processing operations
granting_institution	Universiti Teknologi Malaysia
granting_department	Faculty of Engineering - School of Computing
publishDate	2020
url	http://eprints.utm.my/id/eprint/96437/1/RafidahMuhammadMFABU2020.pdf.pdf
_version_	1747818668298862592

Enhanced dominated completed median ternary pattern for detection of copy-move image forgery against post-processing operations

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