Abstract
This article describes a mathematical method to distinguish computer graphics (CG) from photographic images (PG). Because white balance, CFA and PRNU noise artifacts are the intrinsic properties of optical imaging, we can use these artifacts to reflect camera imaging-specific to some extent. During experiment, we design a 135-D feature set and perform distinguishing process to capture these artifacts. Images selected from relative Columbia University image database are chosen as our experiment database. Experiment result indicates our mathematical method is capable to identify computer generated images from camera produced images with 95.43 % accuracy.
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Acknowledgements
This work is supported in part by: NSF (61272278), Central University special (111087),The major national science and technology special projects (2010ZX03004-003-03), National Nature Science Foundation of China (No. 60832002), Nature Science Foundation of Hubei Province (No. 2009CDB222, No. 2010CDB08602), and Doctoral Fund of Ministry of Education of China (Grant No.200910141110054), E-learning system product development and application, Fundamental Research Funds for the Central Universities (3105005), New mobile multimedia audio and video codec key technology research and development, National level Quality-Engineering Excellent Courses: Computer System and Interface, New Generation broadband wireless mobile information network.
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Gao, S., Zhang, C., Wu, CL., Ye, G., Huang, L. (2014). A Hybrid Feature Based Method for Distinguishing Computer Graphics and Photo-Graphic Image. In: Shi, Y., Kim, HJ., Pérez-González, F. (eds) Digital-Forensics and Watermarking. IWDW 2013. Lecture Notes in Computer Science(), vol 8389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43886-2_22
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DOI: https://doi.org/10.1007/978-3-662-43886-2_22
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