Distinguishing Computer Graphics From Natural Image Based on Benford Model

An improved method with a higher identifying accuracy rate is presented to identify natural images and computer graphics,and the new detection scheme of computer graphics and natural images is based on the Benford model.This algorithm separately calculates the three RGB color channels by probability distribution of the first significant digit of AC coefficient in discrete cosine transform(DCT) domain and correctly classifies the two types of images based on fitting degree of the three curves.Experimental results show that this method can effectively identify natural images and computer graphics.Compared with the existing algorithms,this algorithm has a higher recognition rate,which makes calculation less and easier to implement,and the identifying accuracy rate comes to 97.17%.This provides credible supports for some relative domains such as image forensics and digital anti-fake identification.