The Experts below are selected from a list of 24990 Experts worldwide ranked by ideXlab platform
Stanislav Saic - One of the best experts on this subject based on the ideXlab platform.
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detection of copy move Forgery using a method based on blur moment invariants
Forensic Science International, 2007Co-Authors: Babak Mahdian, Stanislav SaicAbstract:In our society digital images are a powerful and widely used communication medium. They have an important impact on our life. In recent years, due to the advent of high-performance commodity hardware and improved human-computer interfaces, it has become relatively easy to create fake images. Modern, easy to use image processing software enables forgeries that are undetectable by the naked eye. In this work we propose a method to automatically detect and localize duplicated regions in digital images. The presence of duplicated regions in an image may signify a common type of Forgery called copy-move Forgery. The method is based on blur moment invariants, which allows successful detection of copy-move Forgery, even when blur degradation, additional noise, or arbitrary contrast changes are present in the duplicated regions. These modifications are commonly used techniques to conceal traces of copy-move Forgery. Our method works equally well for lossy format such as JPEG. We demonstrate our method on several images affected by copy-move Forgery.
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Detection of copy-move Forgery using a method based on blur moment invariants
Forensic Science International, 2007Co-Authors: Babak Mahdian, Stanislav SaicAbstract:In our society digital images are a powerful and widely used communication medium. They have an important impact on our life. In recent years, due to the advent of high-performance commodity hardware and improved human-computer interfaces, it has become relatively easy to create fake images. Modern, easy to use image processing software enables forgeries that are undetectable by the naked eye. In this work we propose a method to automatically detect and localize duplicated regions in digital images. The presence of duplicated regions in an image may signify a common type of Forgery called copy-move Forgery. The method is based on blur moment invariants, which allows successful detection of copy-move Forgery, even when blur degradation, additional noise, or arbitrary contrast changes are present in the duplicated regions. These modifications are commonly used techniques to conceal traces of copy-move Forgery. Our method works equally well for lossy format such as JPEG. We demonstrate our method on several images affected by copy-move Forgery. © 2006 Elsevier Ireland Ltd. All rights reserved.
Rahul Dixit - One of the best experts on this subject based on the ideXlab platform.
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Detection and localization of inter-frame video forgeries based on inconsistency in correlation distribution between Haralick coded frames
Multimedia Tools and Applications, 2019Co-Authors: Jamimamul Bakas, Ruchira Naskar, Rahul DixitAbstract:With the immensely growing rate of cyber Forgery today, the integrity and authenticity of digital multimedia data are highly at stake. In this work, we deal with forensic investigation of cyber Forgery in digital videos. The most common types of inter-frame Forgery in digital videos are frame insertion, deletion and duplication attacks. A number of significant researches have been carried out in this direction, in the past few years. In this paper, we propose a two-step forensic technique to detect frame insertion, deletion and duplication types of video Forgery. In the first step, we detect outlier frames, based on Haralick coded frame correlation; and in the second step, we perform a finer degree of detection, to eliminate false positives, hence to optimize the Forgery detection accuracy. Our experimental results prove that the proposed method outperforms the state–of–the–art with an average F _1 score of 0.97 in terms of inter–frame video Forgery detection accuracy.
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Review, analysis and parameterisation of techniques for copy–move Forgery detection in digital images
IET Image Processing, 2017Co-Authors: Rahul Dixit, Ruchira NaskarAbstract:Copy–move Forgery is one of the most preliminary and prevalent forms of modification attack on digital images. In this form of Forgery, region(s) of an image is(are) copied and pasted onto itself, and subsequently the forged image is processed appropriately to hide the effects of Forgery. State-of-the-art copy–move Forgery detection techniques for digital images are primarily motivated toward finding duplicate regions in an image. The last decade has seen lot of research advancement in the area of digital image forensics, whereby the investigation for possible forgeries is solely based on post-processing of images. In this study, the authors present a three-way classification of state-of-the-art digital forensic techniques, along with a complete survey of their operating principles. In addition, they analyse the schemes and evaluate and compare their performances in terms of a proposed set of parameters, which may be used as a standard benchmark for evaluating the efficiency of any general copy–move Forgery detection technique for digital images. The comparison results provided by them would help a user to select the most optimal Forgery detection technique, depending on the author requirements.
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On parameterization of block based copy-move Forgery detection techniques
Proceedings of the 2015 Conference on research in adaptive and convergent systems - RACS, 2015Co-Authors: Jatin Wadhwa, Talib Ahemad, Ruchira Naskar, Rahul DixitAbstract:With high increase in cyber-crime along with continuous development in multimedia processing and editing technologies, the credibility of digital images is highly at stake in the present day. Digital images act as the major source of legal evidence in various domains such as media, broadcast and legal industries. Hence any form of illegal modifications to them is intolerable. Recently a lot of researchers have focused on detection and control of digital image forgeries. However the literature lacks a standard way of evaluating and comparing the efficiencies of diverse Forgery detection techniques. In this paper we propose a standard platform for estimating the efficiencies of state-of-the-art digital image Forgery detection techniques. In this work we have dealt with a specific class of digital image Forgery: the Copy-Move Forgery, which is one of most prevalent forms of attack on digital images. We have compared and analyzed different copy-move Forgery detection techniques using the proposed parameters. Our results prove the efficiency of the proposed parameterization and help to select the most suitable scheme according to the user's requirements.
Babak Mahdian - One of the best experts on this subject based on the ideXlab platform.
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detection of copy move Forgery using a method based on blur moment invariants
Forensic Science International, 2007Co-Authors: Babak Mahdian, Stanislav SaicAbstract:In our society digital images are a powerful and widely used communication medium. They have an important impact on our life. In recent years, due to the advent of high-performance commodity hardware and improved human-computer interfaces, it has become relatively easy to create fake images. Modern, easy to use image processing software enables forgeries that are undetectable by the naked eye. In this work we propose a method to automatically detect and localize duplicated regions in digital images. The presence of duplicated regions in an image may signify a common type of Forgery called copy-move Forgery. The method is based on blur moment invariants, which allows successful detection of copy-move Forgery, even when blur degradation, additional noise, or arbitrary contrast changes are present in the duplicated regions. These modifications are commonly used techniques to conceal traces of copy-move Forgery. Our method works equally well for lossy format such as JPEG. We demonstrate our method on several images affected by copy-move Forgery.
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Detection of copy-move Forgery using a method based on blur moment invariants
Forensic Science International, 2007Co-Authors: Babak Mahdian, Stanislav SaicAbstract:In our society digital images are a powerful and widely used communication medium. They have an important impact on our life. In recent years, due to the advent of high-performance commodity hardware and improved human-computer interfaces, it has become relatively easy to create fake images. Modern, easy to use image processing software enables forgeries that are undetectable by the naked eye. In this work we propose a method to automatically detect and localize duplicated regions in digital images. The presence of duplicated regions in an image may signify a common type of Forgery called copy-move Forgery. The method is based on blur moment invariants, which allows successful detection of copy-move Forgery, even when blur degradation, additional noise, or arbitrary contrast changes are present in the duplicated regions. These modifications are commonly used techniques to conceal traces of copy-move Forgery. Our method works equally well for lossy format such as JPEG. We demonstrate our method on several images affected by copy-move Forgery. © 2006 Elsevier Ireland Ltd. All rights reserved.
Ruchira Naskar - One of the best experts on this subject based on the ideXlab platform.
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Detection and localization of inter-frame video forgeries based on inconsistency in correlation distribution between Haralick coded frames
Multimedia Tools and Applications, 2019Co-Authors: Jamimamul Bakas, Ruchira Naskar, Rahul DixitAbstract:With the immensely growing rate of cyber Forgery today, the integrity and authenticity of digital multimedia data are highly at stake. In this work, we deal with forensic investigation of cyber Forgery in digital videos. The most common types of inter-frame Forgery in digital videos are frame insertion, deletion and duplication attacks. A number of significant researches have been carried out in this direction, in the past few years. In this paper, we propose a two-step forensic technique to detect frame insertion, deletion and duplication types of video Forgery. In the first step, we detect outlier frames, based on Haralick coded frame correlation; and in the second step, we perform a finer degree of detection, to eliminate false positives, hence to optimize the Forgery detection accuracy. Our experimental results prove that the proposed method outperforms the state–of–the–art with an average F _1 score of 0.97 in terms of inter–frame video Forgery detection accuracy.
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Review, analysis and parameterisation of techniques for copy–move Forgery detection in digital images
IET Image Processing, 2017Co-Authors: Rahul Dixit, Ruchira NaskarAbstract:Copy–move Forgery is one of the most preliminary and prevalent forms of modification attack on digital images. In this form of Forgery, region(s) of an image is(are) copied and pasted onto itself, and subsequently the forged image is processed appropriately to hide the effects of Forgery. State-of-the-art copy–move Forgery detection techniques for digital images are primarily motivated toward finding duplicate regions in an image. The last decade has seen lot of research advancement in the area of digital image forensics, whereby the investigation for possible forgeries is solely based on post-processing of images. In this study, the authors present a three-way classification of state-of-the-art digital forensic techniques, along with a complete survey of their operating principles. In addition, they analyse the schemes and evaluate and compare their performances in terms of a proposed set of parameters, which may be used as a standard benchmark for evaluating the efficiency of any general copy–move Forgery detection technique for digital images. The comparison results provided by them would help a user to select the most optimal Forgery detection technique, depending on the author requirements.
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On parameterization of block based copy-move Forgery detection techniques
Proceedings of the 2015 Conference on research in adaptive and convergent systems - RACS, 2015Co-Authors: Jatin Wadhwa, Talib Ahemad, Ruchira Naskar, Rahul DixitAbstract:With high increase in cyber-crime along with continuous development in multimedia processing and editing technologies, the credibility of digital images is highly at stake in the present day. Digital images act as the major source of legal evidence in various domains such as media, broadcast and legal industries. Hence any form of illegal modifications to them is intolerable. Recently a lot of researchers have focused on detection and control of digital image forgeries. However the literature lacks a standard way of evaluating and comparing the efficiencies of diverse Forgery detection techniques. In this paper we propose a standard platform for estimating the efficiencies of state-of-the-art digital image Forgery detection techniques. In this work we have dealt with a specific class of digital image Forgery: the Copy-Move Forgery, which is one of most prevalent forms of attack on digital images. We have compared and analyzed different copy-move Forgery detection techniques using the proposed parameters. Our results prove the efficiency of the proposed parameterization and help to select the most suitable scheme according to the user's requirements.
Mohamed Deriche - One of the best experts on this subject based on the ideXlab platform.
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a bibliography of pixel based blind image Forgery detection techniques
Signal Processing-image Communication, 2015Co-Authors: Muhammad Ali Qureshi, Mohamed DericheAbstract:With the advent of powerful image editing tools, manipulating images and changing their content is becoming a trivial task. Now, you can add, change or delete significant information from an image, without leaving any visible signs of such tampering. With more than several millions pictures uploaded daily to the net, the move towards paperless workplaces, and the introduction of e-Government services everywhere, it is becoming important to develop robust detection methods to identify image tampering operations and validate the credibility of digital images. This led to major research efforts in image forensics for security applications with focus on image Forgery detection and authentication. The study of such detection techniques is the main focus of this paper. In particular, we provide a comprehensive survey of different Forgery detection techniques, complementing the limitations of existing reviews in the literature. The survey covers image copy-move Forgery, splicing, Forgery due to resampling, and the newly introduced class of algorithms, namely image retouching. We particularly discuss in detail the class of pixel-based techniques which are the most commonly used approaches, as these do not require any a priori information about the type of tampering. The paper can be seen as a major attempt to provide an up-to-date overview of the research work carried in this all-important field of multimedia. HighlightsA new comprehensive survey of pixel-based Forgery detection methods is presented.A framework for grouping different Forgery detection algorithms is described.We outline the strengths and weaknesses of research efforts in Forgery detection.Numerous tables and figures, analyzing existing algorithms, are discussed.An extensive list of references covering the work of the last decade is provided.
