Study of Image Forgery Detection using Scale Invariant Feature Transform

Images are a crucial source of information and are also used as a legal references and proofs sometimes, but since the availability of it has made easy due to internet hence it is prone to many manipulations and tampering. Image forging refers to the process of changing an original image in order to produce a false image for any fraudulent or other purpose. The most common form of forging is called copy-move forgery, and it consists of clipping or duplicating parts of the original picture and placing them elsewhere on the same image. Forgery detection techniques come in a variety of forms, including block-based and key-point based ones, just as there are various ways that forgeries are carried out. Through comparison with the original picture, the technique suggested in this article aids in identifying image forgeries. Using the Scale Invariant Feature Transform (SIFT) method, separate the invariant features from the original and modified images. The advantages of SIFT over other algorithms is that it helps in reducing computational expenses, increases accuracy, and provides better results.