• Lovish
• Vikas Kumar

This work presented a proposed scheme for image forgery based on image segmentation. It applied SIFT densely to make block-based matching possible and cover all the pixels of the image and also combine method with hashing to improve performance of system. The similarity threshold between feature vectors is one of the most important parameters in detecting CMF. The proposed method to compute the automatic thresholding reduces the false positive and decreases the required time to estimate one threshold for different images in the dataset. The proposed method is compared with other CMFD methods and found better in terms of performance with the help of hashing method. All scenarios are implemented with the help of MATLAB tool.

Image Forgery, Static Feature Transform, Copy Move Forgery, Hashing etc .

"Copy-Move Forgery Detection using Feature Transformation & Hashing Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.458-462, September-2019, Available :http://www.jetir.org/papers/JETIR1907A92.pdf

"Copy-Move Forgery Detection using Feature Transformation & Hashing Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp458-462, September-2019, Available at : http://www.jetir.org/papers/JETIR1907A92.pdf