Review Paper on Development of Forgeries Digital Images by using Illumination Color Classification

Interruptation or manipulation in the digital photographs becomes a common problem in multimedia communication. Interrupted digital images can be rectified with the illuminaton color classification method. Over the years, photographs have been used as document of events as well as proof in legal proceedings. Although some of photographers are able to manipulate the images and make composites of original images, this process requires expert knowledge and demands lot of time. In today’s world, a lot of skillfully developed image editing software’s are available which makes image manipulation and modifications an easy task. This reduces trust in photographs and presents an open question on authenticity of images and photographs. This paper, aims at focusing on the most common forms of image manipulation, which is called as image splicing. Here we propose a forgery detection method which uses inconsistencies in illumination of images. For achieving this, we make use of physics and statistics based illuminant estimators. These illuminant estimates are used to extract features which are then given to a machine-learning technique which supports us in decision-making.