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Image Fakery and Neural Network Based Detection

  • Wei Lu
  • Fu-Lai Chung
  • Hongtao Lu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)

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.

Keywords

Input Image Watermark Image Radius Basis Function Neural Network Altered Area Image Editing Software 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wei Lu
    • 1
    • 2
  • Fu-Lai Chung
    • 2
  • Hongtao Lu
    • 1
  1. 1.Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.Department of ComputingHong Kong Polytechnic UniversityKowloon, Hong KongChina

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