(untitled) (International Journal of Advanced Research in Science, Management and Technology, 2019)
- Now-a-days all the visual forms are become digital for the communication of important data. Due to improvement in computing and network technologies, in past few years we have seen a considerable rise in the accessibility and transmission of digital images using imaging technologies like digital cameras, scanners. This technology is also used for manipulating digital images. There are number of operation in which we can change the image contain, like scaling, rotating, cropping. Preserving originality of image is very difficult due to easily availability and free downloading image editing software. So detecting image forgery is challenging task. In recent years, more data are created in digital form allowing easy control over manipulation due to the technology progress. Unfortunately, this progress may have dragged along a lot of risks, especially the ones related to the security of digital files. A specific form of image forgery operation called “copy-move” is considered one of the most difficult problems in the case of forgery detection. For this case, a part of the image is copied and pasted on another location of the same image to conceal undesirable objects in the scene. A copy-move forgery is created by copying some region and pasting that particular region within the same image, and. In recent years, one of the most actively researched topics in blind image forensics is the detection of copy-move forgery. A considerable number of different algorithms have been proposed focusing on different types of post processed copies. Here, we aim to answer which copy-move forgery detection algorithms and processing steps perform best in various post processing scenarios. In this paper we review different types of methods that are used to detect the copy move forgery in the image also, we propose a scheme to detect the copy-move forgery in an image, mainly by extracting the key points for comparison. The main difference to the traditional methods is that the proposed scheme first segments the test image into semantically independent patches prior to key pointextraction.In this paper, we are representing a review on the existing copy move forgery detection techniques. In this paper, we propose a method that automatically detects duplicated regions in the same image. Duplicated detection is performed by identifying the local characteristics of the images (points of interest) using the Scale Invariant Feature Transform (SIFT) method.