Wavelet-based Image Fingerprinting Scheme Robust to Both Geometric Distortion and Lossy Compression 


Vol. 33,  No. 6, pp. 220-227, Jun.  2008


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  Abstract

In this paper, we propose a novel image fingerprinting scheme based on customer ID embedding and an auto-correlation function (ACF), which is resilient to geometric transform attacks. We embed multi-bits using the random sequence set (RSS) corresponding to the customer ID, which is easy to trace illegal re-distributor of the image. In this scheme, a periodic fingerprinting pattern is embedded in wavelet domain by considering HVS. To restore the geometric attacked image, the ACF of the estimated fingerprint is applied and heuristic algorithms are performed to detect AC peaks correctly. The experimental result fingerprint of the inserted image confirmed that an extraction is successfully made after the geometrical distortion and lossy compression.

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  Cite this article

[IEEE Style]

Y. Seo, Y. Suh, C. Hwang, "Wavelet-based Image Fingerprinting Scheme Robust to Both Geometric Distortion and Lossy Compression," The Journal of Korean Institute of Communications and Information Sciences, vol. 33, no. 6, pp. 220-227, 2008. DOI: .

[ACM Style]

Yong-Seok Seo, Young-Ho Suh, and Chi-Jung Hwang. 2008. Wavelet-based Image Fingerprinting Scheme Robust to Both Geometric Distortion and Lossy Compression. The Journal of Korean Institute of Communications and Information Sciences, 33, 6, (2008), 220-227. DOI: .

[KICS Style]

Yong-Seok Seo, Young-Ho Suh, Chi-Jung Hwang, "Wavelet-based Image Fingerprinting Scheme Robust to Both Geometric Distortion and Lossy Compression," The Journal of Korean Institute of Communications and Information Sciences, vol. 33, no. 6, pp. 220-227, 6. 2008.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880