scholarly journals Comparison and Analysis of Photo Image Forgery Detection Techniques

2012 ◽  
Vol 2 (6) ◽  
pp. 45-56 ◽  
Author(s):  
Murali S
Keyword(s):  
Forgery Detection ◽  
Image Forgery ◽  
Detection Techniques ◽  
Image Forgery Detection ◽  
Comparison And Analysis ◽  
Photo Image

scholarly journals A Review on Copy-Move Image Forgery Detection Techniques

2021 ◽  
Vol 1892 (1) ◽  
pp. 012010
Author(s):  
Zaid Nidhal Khudhair ◽  
Farhan Mohamed ◽  
Karrar A. Kadhim
Keyword(s):  
Forgery Detection ◽  
Image Forgery ◽  
Detection Techniques ◽  
Image Forgery Detection

Passive Aproaches for Detecting Image Tampering: A Review

2015 ◽  
Vol 73 (2) ◽  
Author(s):  
Fatma Salman Hashem ◽  
Ghazali Sulong
Keyword(s):  
Digital Image ◽  
Active Area ◽  
Forgery Detection ◽  
Image Forgery ◽  
Detection Techniques ◽  
Image Tampering ◽  
Highly Active ◽  
Image Forgery Detection ◽  
Hidden Data ◽  
Digital Image Forgery

This paper defines the presently used methods and approaches in the domain of digital image forgery detection.  A survey of a recent study is explored including an examination of the current techniques and passive approaches in detecting image tampering. This area of research is relatively new and only a few sources exist that directly relate to the detection of image forgeries. Passive, or blind, approaches for detecting image tampering are regarded as a new direction of research. In recent years, there has been significant work performed in this highly active area of research. Passive approaches do not depend on hidden data to detect image forgeries, but only utilize the statistics and/or content of the image in question to verify its genuineness. The specific types of forgery detection techniques are discussed below. 

scholarly journals A Survey on Photo Forgery Detection Methods

2018 ◽  
Vol 22 ◽  
pp. 01055
Author(s):  
Bilgehan Gurunlu ◽  
Serkan Ozturk
Keyword(s):  
Image Processing ◽  
Data Hiding ◽  
Detection Methods ◽  
Forgery Detection ◽  
Image Splicing ◽  
Image Forgery ◽  
Detection Techniques ◽  
Passive Detection ◽  
Image Forgery Detection ◽  
Digital Image Forgery

In recent years, digital image forgery detection has become one of the hardest studying area for researchers investigations in the field of information security and image processing. Image forgery detection methods can be divided into two extensive groups such as Active methods and Passive (Blind) methods. Active methods have been used data hiding techniques like watermarking and digital signatures. Passive forensic methods (or Blind) use image statistics or they investigate the attributes of the image to determine the forgeries. Passive detection techniques are also split into three branches; image splicing, image retouching, copy-move. Such image forgery detection methods are focus of this paper.

scholarly journals Reviewing the Effectivity Factor in Existing Techniques of Image Forensics

2017 ◽  
Vol 7 (6) ◽  
pp. 3558
Author(s):  
Shashidhar TM ◽  
KB Ramesh
Keyword(s):  
Image Forensics ◽  
Research Trend ◽  
Forgery Detection ◽  
Image Splicing ◽  
Image Forgery ◽  
Detection Techniques ◽  
Open Research ◽  
Image Forgery Detection ◽  
Attack Scenario ◽  
Research Gap

Studies towards image forensics are about a decade old and various forms of research techniques have been presented till date towards image forgery detection. Majority of the existing techniques deals with identification of tampered regions using different forms of research methodologies. However, it is still an open-end question about the effectiveness of existing image forgery detection techniques as there is no reported benchmarked outcome till date about it. Therefore, the present manuscript discusses about the most frequently addressed image attacks e.g. image splicing and copy-move attack and elaborates the existing techniques presented by research community to resist it. The paper also contributes to explore the direction of present research trend with respect to tool adoption, database adoption, and technique adoption, and frequently used attack scenario. Finally, significant open research gap are explored after reviewing effectiveness of existing techniques.

Image Forgery Detection and Localization

2021 ◽  
pp. 176-182
Author(s):  
Aditi Shedge ◽  
Shaily Shah ◽  
Shubham Pandey ◽  
Mansi Pandey ◽  
Rupali Satpute
Keyword(s):  
Human Brain ◽  
Sources Of Information ◽  
Forgery Detection ◽  
Image Splicing ◽  
Tampering Detection ◽  
Image Forgery ◽  
Detection Techniques ◽  
Image Forgery Detection ◽  
Crime Investigation ◽  
Detection And Localization

A human brain responds at a much faster rate to images and the information it contains. An image is considered as proof of past events that have occurred, but in today's world where editing tools are made available so easily tampering of images and hiding the original content has become too mainstream. The identification of these tampered images is very important as images are considered as vital sources of information in crime investigation and in various other fields. The image forgery detection techniques check the credibility of the image. Various research has been carried out in dealing with image forgery and tampering detection techniques, this paper highlights various the type of forgery and how they can be detected using various techniques. The fusion of various algorithms so that a complete reliable type of algorithm can be developed to deal mainly with copy-move and image splicing forgery. The copy-move and image splicing method are main focus of this paper.

Hierarchical Categorization and Review of Recent Techniques on Image Forgery Detection

2019 ◽  
Author(s):  
V Vinolin ◽  
M Sucharitha
Keyword(s):  
Digital Image Forensics ◽  
Forgery Detection ◽  
Research Papers ◽  
Research Issues ◽  
Image Forgery ◽  
Performance Achievement ◽  
Detection Techniques ◽  
Survey Paper ◽  
Image Forgery Detection ◽  
Hierarchical Categorization

Abstract Information in the form of the image conveys more details than any other form of information. Several software packages are available to manipulate the images so that the authenticity of the images is being questioned. Several image processing approaches are available to create fake images without leaving any visual clue about the forging operation. So, proper image forgery detection tools are required to detect such forgery images. Over the past few years, several research papers were published in the digital image forensics domain for detecting fake images, thus escalating the legitimacy of the images. This survey paper attempts to review the recent approaches proposed for detecting image forgery. Accordingly, several research papers related to image forgery detection are reviewed and analyzed. The taxonomy of image forgery detection techniques is presented, and the algorithms related to each technique are discussed. The comprehensive analysis is carried out based on the dataset used, software used for the implementation and the performance achievement. Besides, the research issues associated with every approach were scrutinized together with the recommendation for future work.

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