AN ADAPTIVE NEURAL NETWORK CLASSIFIED BASED IMAGE FORGERY DETECTION
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Forgery is an illegal modification or reproduction of an image, document signature, legal tender or any other means of recording information. Now-a-days, forgery detection is very important for real world events. In this, forgery detection is performed based on Neural Network. This method requires only a minimum amount of human interaction and provides a crisp statement on the authenticity of the image. It is applicable to images containing two or more people and requires no expert interaction for the tampering decision. The illuminant color using a statistical gray edge method and a physics-based method which exploits the inverse intensity-chromaticity color space. Illuminant maps are treated as texture maps. The information is extracted by the distribution of edges on these maps. In order to describe the edge information, a new algorithm is used based on edge-points and the HOG edge.