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Adaptive Steganography Using 2D Gabor Filters and Ensemble Classifiers

  • Yuan BianEmail author
  • Guangming Tang
  • Shuo Wang
  • Zhanzhan Gao
  • Shiyuan Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10082)

Abstract

In order to preserve the statistical properties of image in all scales and orientations when the embedding changes are constrained to the complicated texture regions, a steganography method is proposed based on 2 dimensional (2D) Gabor filters and Ensemble classifiers. First, we use histogram sequence features of filtered images generated by Gabor filters to describe the texture properties of the image. Then, we design the distortion function using the classification results differences of classifiers between cover and stego. The stego images are used to train the ensemble classifiers using the current popular steganography schemes, such HUGO and S-UNIWARD. Then, the message is embedded using STC (Syndrome Trellis Code). The experimental results show that the proposed scheme can achieve a competitive performance compared with the other steganography schemes HUGO, MVG and S-UNIWARD when using the SRM detection.

Keywords

Adaptive steganography 2D Gabor filter Ensemble classifiers 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Yuan Bian
    • 1
    Email author
  • Guangming Tang
    • 1
  • Shuo Wang
    • 1
  • Zhanzhan Gao
    • 1
  • Shiyuan Chen
    • 1
  1. 1.Institute of Information Science and TechnologyZhengzhouChina

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