Abstract
In this paper, we propose a new feature-based image watermarking scheme based on multiscale theory and the Contourlet transform (CT). We use the multiscale Harris detector to extract stable feature points from the host image. Next, according to feature scale theory, we determine the local feature regions (LFR) and scale the regions to a standard size. We then embed the digital watermark into the Contourlet low frequency area calculated using the pseudo-Zernike moment. The results of our experiments demonstrate that the algorithm results in an invisible watermark and is robust against conventional signal processing (median filtering, sharpening, noise adding, and JPEG compression), geometric attacks (rotation, translation, scaling, row or column removal, shearing, local geometric distortion) and combined attacks.
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Zhu, D., Lv, L. (2015). A New Image Watermarking Algorithm Using the Contourlet Transform and the Harris Detector. In: Zha, H., Chen, X., Wang, L., Miao, Q. (eds) Computer Vision. CCCV 2015. Communications in Computer and Information Science, vol 547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48570-5_42
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DOI: https://doi.org/10.1007/978-3-662-48570-5_42
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