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Halftone Image Steganography with Distortion Measurement Based on Structural Similarity

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Digital Forensics and Watermarking (IWDW 2019)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12022))

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Abstract

For halftone image data hiding, it is difficult to achieve good visual quality and statistical security when high embedding capacity is demanded. In this paper, a secure steganographic scheme for halftone image is proposed, which aims to minimize the embedding distortion on structural similarity. Structural distortions are the ones that affect the most the perception of degradation of a halftone image. To evaluate the structural distortions caused by flipping pixels, halftone image structural similarity (HSSIM) is introduced based on a human visual filter, which is trained by Least-Mean-Square (LMS) approach. Utilizing the HSSIM, a distortion measurement is proposed to evaluate the embedding distortions on both vision and statistics. To minimize the embedding distortions, syndrome-trellis code (STC) is employed in the embedding process. The experimental results have demonstrated that the proposed steganographic scheme can achieve high statistical security with good visual quality without degrading the embedding capacity.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. U1736118), the Key Areas R&D Program of Guangdong (No. 2019B010136002), the Key Scientific Research Program of Guangzhou (No. 201804020068), the Natural Science Foundation of Guangdong (No. 2016A030313350), the Special Funds for Science and Technology Development of Guangdong (No. 2016KZ010103), Shanghai Minsheng Science and Technology Support Program (17DZ1205500), Shanghai Sailing Program (17YF1420000), the Fundamental Research Funds for the Central Universities (No. 17lgjc45).

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Authors and Affiliations

  1. School of Data and Computer Science, Guangdong Key Laboratory of Information Security Technology, Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University, Guangzhou, 510006, China

    Wanteng Liu, Xiaolin Yin, Wei Lu & Junhong Zhang

Authors
  1. Wanteng Liu
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  2. Xiaolin Yin
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  3. Wei Lu
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  4. Junhong Zhang
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Corresponding author

Correspondence to Wei Lu .

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Editors and Affiliations

  1. College of Cybersecurity, Sichuan University, Chengdu, China

    Hongxia Wang

  2. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China

    Xianfeng Zhao

  3. Department of ECE, New Jersey Institute of Technology, Newark, NJ, USA

    Yunqing Shi

  4. Graduate School of Information Study, Korea University, Seoul, Korea (Republic of)

    Hyoung Joong Kim

  5. Department of Information Engineering, University of Florence, Florence, Italy

    Alessandro Piva

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Liu, W., Yin, X., Lu, W., Zhang, J. (2020). Halftone Image Steganography with Distortion Measurement Based on Structural Similarity. In: Wang, H., Zhao, X., Shi, Y., Kim, H., Piva, A. (eds) Digital Forensics and Watermarking. IWDW 2019. Lecture Notes in Computer Science(), vol 12022. Springer, Cham. https://doi.org/10.1007/978-3-030-43575-2_24

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  • DOI: https://doi.org/10.1007/978-3-030-43575-2_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-43574-5

  • Online ISBN: 978-3-030-43575-2

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