• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.548-555
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• 2001

In this paper, we proposed a HVS(human visual system) model-based digital image watermarking which is not only invariant to rotation and translation but also more robust to lossy compression, cropping, and scaling as compared to the conventional method. Fourier transform and log-polar mapping is used to make the proposed algorithm invariant to rotation and translation, and in addition, watermark energy is embedded maximally based on spatial frequency sensitivity of HVS without the deterioration of the invisibility. As a result, the robustness of watermarking is improved both in general image processing operations such as cropping, low pass filtering, and lossy compression and in geometrical transforms such as rotation, translation, and scaling. And, by disjoint embedding of the watermark and the template without intersection, the deterioration of invisibility and robustness is prevented. Experimental results show that proposed watermarking is about 30~75 [%] more robust af compared to the conventional methods.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1510-1519
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• 2005

We proposed a digital watermarking method that it is possible to identify the copyright because the watermark is detected in the first print-scan and to protect a forgery because the watermark is not detected in the second print-scan. The proposed algorithm uses LPM and DFT transform for the robustness to the distortion of pixel value and geometrical distortion. This methods could improve watermark detection performance and image quality by selecting maximum sampling radius in LPM transform. After analyzing the characteristics of print-scan process, we inserted the watermark in the experimentally selected frequency bands that survives robustly to the first print-scan and is not detected in the second print-scan, using the characteristic of relatively large distortion in high frequency bands of DFT As the experimental result, the original proof is possible because average similarity degree 5.13 is more than the critical value 4.0 in the first print-scan. And the detection of forgery image is also possible because average similarity degree 2.76 is less than the critical value 4.0 in the second print-scan.