Copy-move forgery detection in digital image

Copy-move forgery is a specific type of image tampering where a part of the image is copied and pasted somewhere else in the image with the intent to cover an important image feature. Hence, the goal in detection of copy-move forgeries is to detect image areas that are same or extremely similar. In this paper, we investigate the problem of detecting the copy-move forgery and describe an efficient and reliable passive-blind detection method. The method used block-matching procedures, which first divided the image into the same size block, then applied improved singular value decomposition to all of the image blocks to yield a reduced dimension representation for forming the singular value feature matrix of image blocks which was lexicographically sorted. Later, a matching step took place where the aim is to find the duplicated blocks based on their feature vectors. A forgery detection decision is made only if correlation coefficient threshold reached which we set. The experimental result shows that the algorithm has strong detection capability and anti-noise capability.