A zero-watermark scheme with geometrical invariants using SVM and PSO against geometrical attacks for image protection

  • Authors:

  • Hung-Hsu Tsai;Yen-Shou Lai;Shih-Che Lo

  • Affiliations:

  • Department of Information Management, National Formosa University, Yunlin County 632, Taiwan;Department of Information Management, National Formosa University, Yunlin County 632, Taiwan;Department of Industrial Management, National Taiwan University of Science and Technology, Taiwan

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2013

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Abstract

This paper proposes a zero-watermark scheme with geometrical invariants using support vector machine (SVM) classifier against geometrical attacks for image authentication. Here geometrical attacks merely address rotation, scale, and translation (RST) operations on images. The proposed scheme is called the SVM-based zero-watermark (SZW) scheme hereafter. The SZW method makes no changes to original images while embedding the owner signature of images so as to achieve high transparency. Moreover, in order to promote the robustness to RST operations, it integrates the discrete Fourier transform (DFT) with the log-polar mapping (LPM) for finding out RST invariants of images. The SZW method then generates the secret key for a host image via performing a logical operation exclusive disjunction, an exclusive-or (XOR) operation, on the original watermark and a set of the characteristics of the RST invariants of the host image. Subsequently, a trained SVM (TSVM) is regarded as a mapping so that it can memorize the relationships between the set of characteristics of RST invariants and the secret key. During the watermark-extraction process of the SZW method, the TSVM is first fed with the set of characteristics of RST invariants of the watermarked image to get the estimated secret key. The SZW method then extracts the estimated watermark by performing the XOR operation on the set of characteristics of RST invariants and the estimated secret key. Consequently, the SZW method requires no original image while retrieving watermarks. In the paper, the particle swarm optimization (PSO) algorithm is also employed to search for a set of nearly optimal parameters of the SVM. Finally, the experimental results show that, in average, the SZW method outperforms other existing methods against RST attacks under consideration here.