Anzeige
Erschienen in:
2011 | OriginalPaper | Buchkapitel
Discriminating Computer Graphics Images and Natural Images Using Hidden Markov Tree Model
verfasst von : Feng Pan, Jiwu Huang
Erschienen in: Digital Watermarking
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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%.