Fake image detection using CNN

Lately, fake images have become very popular, and it is difficult for people to see them. Due to these fake images, many fields like forensics are facing problems; even social media also became a problem because of the fake images. Many forensics people are trying to overcome this problem. As new types of counterfeit images emerge quickly, the ability to customize new types of counterfeit images is an important, and even challenging, task. In this project, we explore the problem and use machine learning and image editing to overcome this problem. In this paper, we are scheming the LBP on machine learning Convolution Neural Network called LBPNET to get non-fiction images. Here we will first take LBP out of the pictures and train descriptive pictures of LBP with the Convolution Neural Network to produce a training model. Whenever we upload a new test image then that test image will be used in the training model to determine whether the test image contains a fake image or a non-fake image.