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scale invariant feature transform in matlab
no vote
Due to the rapid development and effectiveness of image processing software, it is easy to manipulate and modify digital images. So it's hard to see the authenticity of the given image. Today, important features can be added or removed from images without obvious traces of tampering. As digital cameras and video cameras replace analog counterparts and need for authenticating digital images, content analysis forgery will only increase. For digital photos to be used as evidence of legal issues, or distributed in the media, it is necessary to check the authenticity of the image. In this paper, sift on the letter describes the image forgery detection method. In particular, we focus on the detection of special type digital forgery -- copy mobile attack, in a copy moveimage forgery method; a part of the image is copied in different positions of the same image in thenpasted. Based on an improved algorithm, scale invariant features transform (SIFT) is used to detect the forgery of this clone. After this technology is applied to reduce the input image of yielda, key point detection and feature descriptor are applied to match the three-dimensional representation of all key points. This method can let us all know whether a mobile attack occurs. In addition, we also use clustering analysis to find the matching points in givesoutput.
bono123
2016-08-23
0
1
Detection of tampered region in Digital Image
4.0
Digital images are easy to manipulate and edit due to the availability of powerful image processing and editing software. Today, important features can be added or removed from imagewithout, which leaves any obvious traces of tampering. As the analog counterparts of digital cameras and video cameras, it is necessary to verify their contents when they are used to verify digital images, and the analysis forgery will only increase. Malicious manipulation and digital forgeries detection are the main topics of this paper. In particular, we focus on the special type of digital forgery, in which a part of the image detected by copy mobile attack is copied and pasted somewhere, trying to cover up an important image feature and other parts of the image. In this paper, we investigate the problem of detecting replica mobile forgery and describe an efficient and reliable detection method. This method may successfully detect the forgery part, even when the copied region is enhanced / retouched to merge it with the background, when the lossy format such as JPEG forgery image issaved. The performance of the method is demonstratedon several forged images.
bono123
2016-08-23
0
1
image forgery detection
no vote
image forgery detection using SIFT keypoint feature extraction which one of the most robust techniques to detect forgery in digital image. the source code is written in MATLAB.
bono123
2014-04-28
2
1
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