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http://dx.doi.org/10.13089/JKIISC.2014.24.2.311

New feature and SVM based advanced classification of Computer Graphics and Photographic Images  

Jeong, DooWon (Center for Information Security Technologies(CIST), Korea University)
Chung, Hyunji (Center for Information Security Technologies(CIST), Korea University)
Hong, Ilyoung (Seoul Supreme Prosecutors' Office)
Lee, Sangjin (Center for Information Security Technologies(CIST), Korea University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.24, no.2, 2014 , pp. 311-318 More about this Journal
Abstract
As modern computer graphics technology has been developed, it is hard to discriminate computer graphics from photographic images with the naked eye. Advances in graphics technology has brought a lot of convenience to human, it has side effects such as image forgery, malicious edit and fraudulent means. In order to cope with such problems, studies of various algorithms using a feature that represents a characteristic of an image has been processed. In this paper, we verify directly the existing algorithm, and provide new features based a noise that represents the characteristics of the computer graphics well. And this paper introduces the method of using SVM(Support Vector Machine) with features proposed in previous research to improve the discrimination accuracy.
Keywords
JPEG; Computer graphics; Photographic images; Features; SVM;
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