Image Authentication by Detecting Traces of Demosaicing
With increasing technical advances, computer graphics are becoming more photorealistic. Therefore, it is important to develop methods for distinguishing between actual pho -tographs from digital cameras and computer generated im-ages. We describe a novel approach to this problem. Rather than focusing on the statistical differences between the im-age textures, we recognize that images from digital cameras contain traces of resampling as a result of using a color fil-G 1,1 R 1,2 G 1,3 R 1,4 G 1,5 R 1,6 B 2,1 G 2,2 B 2,3 G 2,4 B 2,5 G 2,6 G 3,1 R 3,2 G 3,3 R 3,4 G 3,5 R 3,6 B 4,1 G 4,2 B 4,3 G 4,4 B 4,5 G 4,6 G 5,1 R 5,2 G 5,3 R 5,4 G 5,5 R 5,6 B 6,1 G 6,2 B 6,3 G 6,4 B 6,5 G 6,6 1000 800 Energy 600 400 200 00 0.2 0.4 0.6 0.8 1 Normalized Frequency ter array with demosaicing algorithms. We recognize that estimation of the actual demosaicing parameters is not nec-essary; rather, detection of the presence of demosaicing is the key. The in-camera processing (rather than the image content) distinguishes the digital camera photographs from computer graphics. Our results show high reliability on a standard test set of JPEG compressed images from con-sumer digital cameras. Further, we show the application of these ideas for accurately localizing forged regions within digital camera images.
Image Sensors,Demosaicing,PIM ,PRCG,forged image regions