Results 221 to 230 of about 499 (253)

A Non-intrusive Method for Copy-Move Forgery Detection

2011
The issue of verifying the authenticity and integrity of digital images is becoming increasingly important. Copy-move forgery is one type of image tempering that is commonly used for manipulating digital content; in this case, some part of an image is copied and pasted on another region of the image. Using a non-intrusive approach to solve this problem
Najah Muhammad, Muhammad Hussain 0001, Muhammad Ghulam, George Bebis   +3 more
openaire   +1 more source

Copy–Move Forgery Detection by Matching Triangles of Keypoints

IEEE Transactions on Information Forensics and Security, 2015
Copy–move forgery is one of the most common types of tampering for digital images. Detection methods generally use block-matching approaches, which first divide the image into overlapping blocks and then extract and compare features to find similar ones, or point-based approaches, in which relevant keypoints are extracted and matched to each other to ...
Edoardo Ardizzone, Alessandro Bruno, Giuseppe Mazzola   +2 more
openaire   +2 more sources

Copy-move forgery detection from printed images

SPIE Proceedings, 2014
Counterfeiting digital images through a copy-move forgery is one of the most common ways of manipulating the semantic content of a picture, whereby a portion of the image is copy-pasted elsewhere into the same image. It could happen, however, instead of a digital image only its analog version may be available. Scanned or recaptured (by a digital camera)
Irene Amerini, Roberto Caldelli, Alberto Del Bimbo, Andrea Di Fuccia, Luigi Saravo, Anna Paola Rizzo   +5 more
openaire   +1 more source

Copy-move forgery detection based on scaled ORB

Multimedia Tools and Applications, 2015
To solve the problem of the false matching and low robustness in detecting copy-move forgeries, a new method was proposed in this study. It involves the following steps: first, establish a Gaussian scale space; second, extract the orientated FAST key points and the ORB features in each scale space; thirdly, revert the coordinates of the orientated FAST
Ye Zhu, Xuanjing Shen, Haipeng Chen 0002
openaire   +1 more source

Fan Search for Image Copy-Move Forgery Detection

2014
Image forgery detection is currently one of the interested research fields of image processing. Copy-Move (CM) forgery is one of the most commonly techniques. In this paper, we propose an efficient methodology for fast CM forgery detection. The proposed method accelerates blocking matching strategy.
Sondos M. Fadl, Noura A. Semary, Mohiy M. Hadhoud   +2 more
openaire   +1 more source

JPEG compression model in copy-move forgery detection

2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), 2017
The integrity of visual data is important for the credibility of news media and especially when used as an evidence in court or during criminal investigation. The common way to manipulate image content is copying an object and pasting in another location of the same image.
Adam Novozámský, Michal Sorel
openaire   +1 more source

Copy-move forgery detection based on deep learning

2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2017
Copy-move forgery detection (CMFD) is probably one of the most active research areas within the blind image forensics field. Among existing algorithms, most of them are based on block and key-point methods, or combination of them. Recently, some deep convolutional neural networks methods have been applied in the image classification, image forensic ...
Junlin Ouyang, Yizhi Liu, Miao Liao
openaire   +1 more source

Efficient Dense-Field Copy–Move Forgery Detection

IEEE Transactions on Information Forensics and Security, 2015
We propose a new algorithm for the accurate detection and localization of copy–move forgeries, based on rotation-invariant features computed densely on the image. Dense-field techniques proposed in the literature guarantee a superior performance with respect to their keypoint-based counterparts, at the price of a much higher processing time, mostly due
COZZOLINO, DAVIDE, POGGI, GIOVANNI, VERDOLIVA, LUISA   +2 more
openaire   +2 more sources

Survey on image copy-move forgery detection

Multimedia Tools and Applications, 2023
Mayank Verma, Durgesh Singh 0001
openaire   +1 more source

A review on copy move image forgery detection techniques

2014 IEEE 11th International Multi-Conference on Systems, Signals & Devices (SSD14), 2014
With the advent of powerful image editing tools, manipulating images and changing their content is becoming a trivial task. It is now possible to add, modify, or remove important features from an image without leaving any perceptual traces of tampering.
Muhammad Ali Qureshi, Mohamed A. Deriche
openaire   +1 more source