Abstract
A large number of sophisticated, yet easily accessible computer graphics softwares (STUDIO MAX, 3D MAYA, etc.) have been developed in the recent past. The images generated with these softwares appear to be realistic and cannot be distinguished from natural images visually. As a result, distinguishing between photographic images (PIM) and Photo-realistic computer generated (PRCG) images of real world objects has become an active area of research. In this paper, we propose that “a computer generated image” would have the features corresponding to a “completely tampered image”, whereas a camera generated picture would not. So, the differentiation is done on the basis of tampering localization features viz., block measure factors based on JPEG compression and re-sampling. It has been observed experimentally, that these measure factors vary for a PIM from a PRCG image. The experimental results show that the proposed simple and robust classifier is able to differentiate between PIM and PRCG images with an accuracy of 96 %.
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Ayyalasomayajula, R.S., Pankajakshan, V. (2017). Differentiating Photographic and PRCG Images Using Tampering Localization Features. In: Raman, B., Kumar, S., Roy, P., Sen, D. (eds) Proceedings of International Conference on Computer Vision and Image Processing. Advances in Intelligent Systems and Computing, vol 460. Springer, Singapore. https://doi.org/10.1007/978-981-10-2107-7_39
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DOI: https://doi.org/10.1007/978-981-10-2107-7_39
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