摘要
As the advent and growing popularity of image rendering software,photorealistic computer graphics are becoming more and more perceptually indistinguishable from photographic images.If the faked images are abused,it may lead to potential social,legal or private consequences.To this end,it is very necessary and also challenging to find effective methods to differentiate between them.In this paper,a novel leading digit law,also called Benford's law,based method to identify computer graphics is proposed.More specifically,statistics of the most significant digits are extracted from image's Discrete Cosine Transform(DCT) coefficients and magnitudes of image's gradient,and then the Support Vector Machine(SVM) based classifiers are built.Results of experiments on the image datasets indicate that the proposed method is comparable to prior works.Besides,it possesses low dimensional features and low computational complexity.
As the advent and growing popularity of image rendering software, photorealistic computer graphics are becoming more and more perceptually indistinguishable from photographic images. If the faked images are abused, it may lead to potential social, legal or private consequences. To this end, it is very necessary and also challenging to find effective methods to differentiate between them. In this paper, a novel leading digit law, also called Benford＇s law, based method to identify computer graphics is proposed. More specifically, statistics of the most significant digits are extracted from image＇s Discrete Cosine Transform （DCT） coefficients and magnitudes of image＇s gradient, and then the Support Vector Machine （SVM） based classifiers are built. Results of experiments on the image datasets indicate that the proposed method is comparable to prior works. Besides, it possesses low dimensional features and low computational complexity.
