Detection of Copy-Move Forgery in Digital Images a (original) (raw)

Copy - Move Forgery Detection in Digital Images

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2023

In today's day today life digital images are available everywhere and it is very easy to manipulate these digital images by using powerful editing software. Now a day's many people add, crop or remove important features from an image without leaving any proof of fake images. There are many techniques used for forgery detection. One of the technique most commonly used is Copy-Move forgery in which coping a some part of image and pasting it into the same image in order to hide some data or part of an image and other most commonly used technique is staganalysis in which some message is hidden inside the image which is not easily possible to see with naked human eye. In this paper we search the problem of detecting the forgery and describe robust detection method. this method successfully detect the forged part even when the copied area is edited to combine it with the background of an image and even if the forged image is saved in the JPEG format.

IJERT-Copy-Move Forgery Attack Detection in Digital Images

International Journal of Engineering Research and Technology (IJERT), 2015

https://www.ijert.org/copy-move-forgery-attack-detection-in-digital-images https://www.ijert.org/research/copy-move-forgery-attack-detection-in-digital-images-IJERTV4IS061110.pdf In today's era of digital technology, security becomes a prominent issue while transferring data from one place to another place. A large amount of data is passed in form of digital images in various areas like military, security agencies, secured networks etc. With the advancement in technology & editing tools like Photoshop, Corel Draw and other software tools, it is very easy to tamper the images. Image forensics determines the authenticity of the images. Image tampering (manipulation) is also called as image forgery. Copy move forgery is more critical in which one part of the image is copied and pasted into another location of the same image to hide details. It can be a crucial task where images are used as evidence like court, medical department etc. Detection of forgery can be difficult if forger has applied some post processing operations like resizing, filtering, rotation, JPEG compression etc. It is seen that image forgery can results into various security issues and hence an efficient system is required to detect the forgery into images. In this paper, we have discussed the various copy move forgery detection techniques which includes Block based & Key Point based techniques. Keywords-Copy-move forgery, Image forensics, Block-based methods, , Feature-based methods.

STUDY OF VARIOUS COPY MOVE FORGERY ATTACK DETECTION TECHNIQUES IN DIGITAL IMAGES

In today’s era of digital technology, security becomes a prominent issue while transferring data from one place to another place. A large amount of data is passed in form of digital images in various areas like military, security agencies, secured networks etc. With the advancement in technology & editing tools like Photoshop, Corel Draw and other software tools, it is very easy to tamper the images. Image forensics determines the authenticity of the images. Image tampering (manipulation) is also called as image forgery. Copy move forgery is more critical in which one part of the image is copied and pasted into another location of the same image to hide details. It can be a crucial task where images are used as evidence like court, medical department etc. Detection of forgery can be difficult if forger has applied some post processing operations like resizing, filtering, rotation, JPEG compression etc. It is seen that image forgery can results into various security issues and hence an efficient system is required to detect the forgery into images. In this paper, we have discussed the various copy move forgery detection techniques which includes Block based & Key Point based techniques

DIGITAL IMAGE FORGERY DETECTION

Digital images are the foremost important source of information. The availability of powerful image processing software's make it relatively easy to make further as manipulate and make digital image forgery of 1 or multiple images. In today's world it's easy to develop image forgery by adding or removing some element from the image which ends in image tampering. A copy-move is made by copying and pasting content within the identical image, and post operating it. The detection of copy-move forgeries has become one in all the foremost actively researched topics in image forensics .The key objective of the proposed method is to review the effect of various styles of tampering on the digital image, detect image forgery by copy-move method under many varieties of attacks by combining block-based and feature-based method and accurately locating the duplicated region.

Copy Move Forgery Detection on Digital Images

International Journal of Computer Applications, 2014

In today's scenario forging of the Digital images has become a common phenomena. The availability of low cost manipulation software also boost to this practice. The foremost practice of manipulating the digital images employed by the most forgerer is the copy move forgery. Copy move forgery is basically concerned with concealing or duplicating one region in an image by pasting certain portions of the same image on it. Numerous Algorithms are proposed to detect copy move forgery in digital images. In this paper an enhanced way to detect copy move forgery is proposed. It is analyzed that block based methods are secured against noise and JPEG compression where as feature based methods are robust to the rotation and scaling operations .The proposed approach use both block based method and feature based method to increase the accuracy rate of forgery detection. The Proposed method employed DCT and SIFT to extract features from image and matching those collected features to detect forgery on image and also perform the localization of the Forged Regions in the Digital Image.

Image Copy Move Forgery Detection: A Review

International Journal of Future Generation Communication and Networking

Technological development in digital world has led to a huge increase in the popularity of digital images in all domains of life. However, sophisticated and easy to use photo editing software tools have made manipulation of images very easy. Thus there is a need to authenticate images especially in legal matters. The field of image authentication and forgery detection has gained huge popularity lately. A key domain in this regard is copy-move forgery detection. Copy move forgery involves copying a portion of an image and pasting it to a different location in same image, with a purpose to conceal facts. In this paper we attempt to review recent developments in the field of copy move detection. This paper dwells on the detection of copy move forgery based on block based and key point methods, and give a detailed comparison of the state of art techniques.

Copy-Move Image Forgery Detection a Review

International Journal of Image, Graphics and Signal Processing, 2016

Due to the availability of various image processing tools forgery over an image can be performed very easily but very difficult to identify. In copy-move forgery, a segment is copied from the original image and pasted at some other location on the same image to hide significant objects of image or to bring additional information which is originally not present in image. Nowadays, this forgery technique is drawing researcher"s attention. Till now many solutions are presented by researchers to detect such type of forgery in images. Several post-processing operations like rotation, alteration in intensity, noise addition, filtering and blurring can be applied over copy-moved segment which makes detection of forgery very difficult. Copy-move forgery detection is mainly based on finding similarity present in an image and establish a relationship between genuine image parts and pasted portion of the image. This paper is centralized towards providing survey to forgery detection techniques based on different block-based methods. In block-based methods image is divided in blocks of fixed dimension and further features are extracted corresponding to each block of image. Forged blocks are identified utilizing the similarity present between feature vectors.

Techniques of Copy Move Forgery Image Detection -Review

— Copy Move forgery is common type of image forgery. A part of image is replaced (copied and pasted in the same image) with another part from the same image. The purpose behind this kind of forgery is may be to create duplication or to hide some particular detail of the image. Using some image editing tools someone can easily tamper the image. This results into loss of image authenticity or image integrity. This paper discusses on different methods used for detection of image forgery. A considerable number of different algorithms have been proposed focusing on different types of post processed copies. Here the aim is to discuss on different copy-move forgery detection algorithms.

A Forensic Technique to Detect Copy-Move Forgery Based on Image Statistics

2020

The proliferation of easy multimedia editing tools has ruined the trust in what we see. Forensic techniques are proposed to detect forgeries unnoticeable by naked human eyes. In this paper, we focus on a specific copy-move forgery attack that happens to alter portions within an image. It may be aimed to hide any sensitive information contained in a particular image portion or misguide the facts. Here, we propose to exploit the image's statistical properties, specifically, mean and variance, to detect the forged portions. A block-wise comparison is made based on these properties to localize the forged region called a prediction mask. Post-processing methods have been proposed to reduce false positives and improve the accuracy(F-score) of the prediction mask. This decrease in FPR in the final result is comes from post processing method of overlaying multiple masks with different values of threshold and block size of the sliding window.