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Copy Move Forgery Detection Using SIFT & RANSAC Algorithm

version 1.0.1 (931 KB) by Thilak Babu Sayila
Image forgery detection for high resolution images using SIFT and RANSAC algorithm

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Updated 02 May 2019

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Cloning (copy-move forgery) is a malicious
tampering attack with digital images where a part of image is copied and pasted within the image to conceal the important details of image without any obvious traces of manipulation. This type of tampering attacks leaves a big question of authenticity of images to the forensics. Many techniques are proposed in the past few years after powerful software’s are developed to manipulate the image. The proposed scheme is involved with both the block based and feature point extraction based techniques to extract the forged regions more accurately. The proposed algorithm mainly involves in matching the tentacles of same features extracted from each block by computing the dot product between the unit vectors. Random Sample Consensus (RANSAC) algorithm is used to extract the matched regions. The experimental result of the algorithm which is proposed indicates that, it can extract more accurate results compared with existing.
forgery detection methods.

Cite As

Ramu, Gonapalli, and S. B. G. Thilak Babu. “Image Forgery Detection for High Resolution Images Using SIFT and RANSAC Algorithm.” 2017 2nd International Conference on Communication and Electronics Systems (ICCES), IEEE, 2017, doi:10.1109/cesys.2017.8321205.

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Babu, S. B. G. Tilak, and Ch. Srinivasa Rao. “Texture and Steerability Based Image Authentication.” 2016 11th International Conference on Industrial and Information Systems (ICIIS), IEEE, 2016, doi:10.1109/iciinfs.2016.8262925.

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MATLAB Release Compatibility
Created with R2019a
Compatible with any release
Platform Compatibility
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