Survey on blind image forgery detection

Qazi, Tanzeela; Hayat, Khizar; Khan, Samee U.; Madani, Sajjad A.; Khan, Imran Ali; Kołodziej, Joanna; Li, Hongxiang; Lin, Weiyao; Yow, Kin Choong; Xu, Cheng‐Zhong

doi:10.1049/iet-ipr.2012.0388

Cited by 97 publications

(50 citation statements)

References 62 publications

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“…Considering the recent related works in this area, we will firstly, have a brief outlook on the survey papers. Qazi, Tanzeela et al [3] presented in the survey of basic blind image detection techniques, in which they discussed techniques regarding the exposure of image forgeries and concept like splicing and retouching. Al-Qershi et al [4] discussed the similar scenario of image forgery detection techniques.…”

Section: Related Workmentioning

confidence: 99%

Block and Fuzzy Techniques Based Forensic Tool for Detection and Classification of Image Forgery

Hashmi¹,

Keskar²

2015

Journal of Electrical Engineering and Technology

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-In today's era of advanced technological developments, the threats to the authenticity and integrity of digital images, in a nutshell, the threats to the Image Forensics Research communities have also increased proportionately. This happened as even for the 'non-expert' forgers, the availability of image processing tools has become a cakewalk. This image forgery poses a great problem for judicial authorities in any context of trade and commerce. Block matching based image cloning detection system is widely researched over the last 2-3 decades but this was discouraged by higher computational complexity and more time requirement at the algorithm level. Thus, for reducing time need, various dimension reduction techniques have been employed. Since a single technique cannot cope up with all the transformations like addition of noise, blurring, intensity variation, etc. we employ multiple techniques to a single image. In this paper, we have used Fuzzy logic approach for decision making and getting a global response of all the techniques, since their individual outputs depend on various parameters. Experimental results have given enthusiastic elicitations as regards various transformations to the digital image. Hence this paper proposes Fuzzy based cloning detection and classification system. Experimental results have shown that our detection system achieves classification accuracy of 94.12%. Detection accuracy (DAR) while in case of 81×81 sized copied portion the maximum accuracy achieved is 99.17% as regards subjection to transformations like Blurring, Intensity Variation and Gaussian Noise Addition.

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Section: Related Workmentioning

confidence: 99%

Block and Fuzzy Techniques Based Forensic Tool for Detection and Classification of Image Forgery

Hashmi¹,

Keskar²

2015

Journal of Electrical Engineering and Technology

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“…Image forgery can be traced back to as early as 1840s when Hippolyte Bayard created the fake image, in which he was shown committing a suicide [3]. Forged images, often leaving no visual clues of having been forged, can be indistinguishable from the original images.…”

Section: Introductionmentioning

confidence: 99%

“…Owing to such sophisticated digital image editing software tools, the establishment of the authenticity of a digital image has become a challenging task, encompassing a variety of issues. In this age of illusions, there is a huge question mark over the use of multimedia data as evidence in the courts of law [3].…”

Section: Introductionmentioning

confidence: 99%

“…Digital image forensics, or the digital image forgery detection, is a field that analyses images of a particular scenario to establish credibility and authenticity through a variety of means [3]. It is becoming a popular field that it can Manuscript received April 2, 2015; revised September 22, 2015.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, detecting the image interpolation forgeries by differences of the image frequency is proposed [6]. Also, researches have emerged that review a number of state-of-the-art digital image forgeries detection schemes [3], [4], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

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An Implementation and Pragmatic Analysis of the Digital Image Forgery Detection Schemes

Kim¹,

Lee²

2015

IJFCC

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Abstract-We select the most effective and remarkable schemes among the state-of-the-art digital forgery detection schemes and implement a system based on these schemes. With that, we compare the advantages and limitations of each scheme by experimental analysis. As a result, the detection rate of the schemes is dependent of the parameters of the schemes and the forgery method of the image, although the schemes succeed to detect most of the forged images. Also, a number of forged images are not detected which are off the detection points of the schemes.Index Terms-Digital image forgery, forgery detection, digital forensics, forensic implementation, forensic practice (alphabetical order).

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Digital Image Forensics-Gateway to Authenticity: Crafted with Observations, Trends and Forecasts

Jindal

Singh

2019

Handbook of Multimedia Information Security: Techniques and Applications

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Survey on blind image forgery detection

Cited by 97 publications

References 62 publications

Block and Fuzzy Techniques Based Forensic Tool for Detection and Classification of Image Forgery

Block and Fuzzy Techniques Based Forensic Tool for Detection and Classification of Image Forgery

An Implementation and Pragmatic Analysis of the Digital Image Forgery Detection Schemes

Digital Image Forensics-Gateway to Authenticity: Crafted with Observations, Trends and Forecasts

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