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Performance analysis of robust watermarking using linear and nonlinear feature matching

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Abstract

Recently, the feature point matching based watermarking techniques have been paying attention for resisting the geometric attacks. We present a performance analysis of robust watermarking using the linear and nonlinear features. In particular, we consider the geometric attacks and the signal processing attacks for the image watermarking. In order to analyze the efficiency of linear and nonlinear features, we employ the linear and the nonlinear feature matching technique in the image watermarking. The extracted feature points can survive against several attacks, therefore, those can be used as reference points for restoration before the extraction of the watermark information. For blindness and robustness, we embed the watermark into the low-band of the discrete cosine transform (DCT) domain. Experimental results show our performance analysis of watermarking methods using the linear and nonlinear feature matching, against the geometric attacks and the signal processing attacks. These include the JPEG compression, the filtering attacks, and so on.

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Notes

  1. SURF: Speeded Up Robust Features [4].

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Authors and Affiliations

  1. Le Quy Don Technical University, 236 Hoang Quoc Viet Street, Ha Noi City, Vietnam

    Ta Minh Thanh & Luu Hong Dung

  2. Tokyo Institute of Technology, 2-12-2, Ookayama, Meguro-ku, Tokyo, 152-8552, Japan

    Keisuke Tanaka

  3. Military Metrology Department (MMD), Ha Noi City, Vietnam

    Nguyen Tuan Tai

  4. Academy of Cryptography Techniques, Ha Noi City, Vietnam

    Hai Nguyen Nam

Authors
  1. Ta Minh Thanh
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  2. Keisuke Tanaka
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  3. Luu Hong Dung
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  4. Nguyen Tuan Tai
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  5. Hai Nguyen Nam
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Correspondence to Ta Minh Thanh.

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Thanh, T.M., Tanaka, K., Dung, L.H. et al. Performance analysis of robust watermarking using linear and nonlinear feature matching. Multimed Tools Appl 77, 2901–2920 (2018). https://doi.org/10.1007/s11042-017-4435-1

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  • DOI: https://doi.org/10.1007/s11042-017-4435-1

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