Image fakery and neural network based detection

Authors:
Wei Lu;Fu-Lai Chung;Hongtao Lu
Affiliations:
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Computing, Hong Kong Polytechnic University, Kowloon, Hong Kong, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II
Year:
2006

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Abstract

By right of the great convenience of computer graphics and digital imaging, it is much easier to alter the content of an image than before without any visually traces. Human has not believed what they see. Many digital images can not be judged whether they are real or feigned visually, i.e., many fake images are produced whose content is feigned. In this paper, firstly, image fakery is introduced, including how to produce fake images and its characters. Then, a fake image detection scheme is proposed, which uses radial basis function (RBF) neural network as a detector to make a binary decision on whether an image is fake or real. The experimental results also demonstrated the effectiveness of the proposed scheme.