Date of Publication :17th November 2017

Abstract: As we are living in the today’s world where all type of advancements are becoming possible and at the same time the use of images has been increasing day by day in our lives by means of uploading and transferring. The manipulation of images also increasing simultaneously. The victims of Image forgery increasing on daily basis. In this paper, we are performing a review of this Image forgery types and methods to detect image forgery. There are two kinds of techniques for detecting image forgery: one is the active method, and the other is passive method. The main types of Image forgeries are Image Splicing, Copy-Move forgery and image retouching. These techniques used mainly for making tempered photographs. As the Image forgery with sophisticated technology is growing it is very much necessary to develop tools for detection of the original image and the region of forgery. We study one of the most powerful technique with a classifier based on Neural Networks. The proposed framework involves key steps like image acquisition, future extraction and classification algorithm. This method also monitors parameters like accuracy, precision etc. The implementation of proposed method meets the future needs in image forensics and reduces the risk of digital images.

Reference :