Discriminating computer graphics images and natural images using hidden Markov tree model

  • Authors:

  • Feng Pan;Jiwu Huang

  • Affiliations:

  • Guangdong Key Lab of Information Security Technology, Guangzhou, China and School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, China;Guangdong Key Lab of Information Security Technology, Guangzhou, China and School of Information Science and Technology, Sun Yat-Sen University, Guangzhou, China

  • Venue:
  • IWDW'10 Proceedings of the 9th international conference on Digital watermarking
  • Year:
  • 2010

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Abstract

People can make highly photorealistic images using rendering technology of computer graphics. It is difficult to human eye to distinguish these images from real photo images. If an image is photorealistic graphics, it is highly possible that the content of the image was made up by human and the reliability of it becomes low. This research field belongs to passive-blind image authentication. Identifying computer graphics images is an important problem in image classification, too. In this paper, we propose using HMT(hidden Markov tree) to classifying natural images and computer graphics images. A set of features are derived from HMT model parameters and its effect is verified by experiment. The average accuracy is up to 84.6%.