Identifying computer generated and digital camera images using fractional lower order moments

With the use of advanced computer graphics rendering software, computer generated images have become difficult to be visually differentiated from natural images captured using digital cameras. The need for automatically distinguishing computer generated images from natural images is becoming significantly important for image forensic techniques. In this paper, a novel approach is proposed to differentiate the two image categories. An alpha-stable distribution model is built to characterize the wavelet decomposition coefficients of natural images. The suitability of the model is then illustrated. The fractional lower order moments in the image wavelet domain are extracted and evaluated with the support vector machine classifier. The experimental results show that the proposed method performs better than the previous higher-order statistical approaches.