Markov-based image forensics for photographic copying from printed picture

Nowadays, photographic-copying technique is very popular along with the rapid development of the image-capturing device, especially digital camera. As a result, the recaptured images, i.e., images taken from real-scene images displayed on various medium, e.g., LCD screen, are used in illegal cases now and then. In this paper, by comparing the recaptured images with their corresponding real-scene images, we find the recapturing procedure changes the statistics of the images. Then the Markov process based features extracted from the Discrete Cosine Transform(DCT) coefficients array are proposed to characterize this changes. During experimentation, a large and typical image dataset, which consisted of 3994 real-scene images and 3994 recaptured images that are taken from printed pictures with diversified image contents and camera models, is build and used for training and testing the classifier Support Vector Machine(SVM). Experimental results show that the proposed forensics scheme performs very well and outperforms the state-of-art methods.