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A neighborhood-characteristic-based detection model for statistical fragile watermarking with localization

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Abstract

Statistical fragile watermarking is capable of accurately locating tampered pixels and resisting the collage attack. However, the constraint of the tamper ratio may be too stringent. This paper proposes a neighborhood characteristic based detection model for statistical fragile watermarking to lift the constraints of the tampered area from 4% to 14% of the host image. The neighborhood characteristic is used to effectively decrease the probability of false rejection, while the low probability of false acceptance is guaranteed by selecting proper threshold. The tamper detection performance of the proposed detection model is analytical analyzed in the different conditions. Analytical and experimental results demonstrate that the neighborhood characteristic based detection model effectively reduce the total number of false decisions and detect the tampered pixels with high probability.

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Acknowledgements

This work is supported in part by the National Natural Science Foundation of China (Grant No. 60970122, 60772084, 60702025), the National S & T Major Project of China (Grant No.2008ZX05046-01), and by the Research Fund for the Doctoral Program of Higher Education (Grant No. 20090184120021, 20070613024)

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Authors and Affiliations

  1. Sichuan Key Lab of Signal and Information Processing, Southwest Jiaotong University, Chengdu, 610031, China

    Hongjie He & Jiashu Zhang

  2. Department of Electrical Engineering, University of Tulsa, Tulsa, OK, 74104, USA

    Heng-Ming Tai

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  1. Hongjie He
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  2. Jiashu Zhang
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  3. Heng-Ming Tai
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Correspondence to Hongjie He.

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He, H., Zhang, J. & Tai, HM. A neighborhood-characteristic-based detection model for statistical fragile watermarking with localization. Multimed Tools Appl 52, 307–324 (2011). https://doi.org/10.1007/s11042-010-0474-6

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  • DOI: https://doi.org/10.1007/s11042-010-0474-6

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