Neural-network-based zero-watermark scheme for digital images

Sang Jun; Xiaofeng Liao; Mohammad S. Alam

doi:10.1117/1.2354076

1 September 2006 Neural-network-based zero-watermark scheme for digital images

Sang Jun, Xiaofeng Liao, Mohammad S. Alam

Author Affiliations +

Optical Engineering, Vol. 45, Issue 9, 097006 (September 2006). https://doi.org/10.1117/1.2354076

Abstract

Digital watermarking has been widely studied for the copyright protection of digital multimedia data. In traditional digital image watermarking techniques, a watermark signal is inserted into the host image, which generally introduces visual quality degradation. On the contrary, zero-watermark techniques extract some features from the host image and use them for watermark detection, instead of watermark embedding. In this method, the distortion problem to the host image due to watermark embedding is eliminated. The zero-watermark scheme proposed in this work employs neural networks for features extraction. It can be used for automatic piracy detection as well as copyright demonstration if it is associated with a copyright authentication center.

©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Sang Jun, Xiaofeng Liao, and Mohammad S. Alam "Neural-network-based zero-watermark scheme for digital images," Optical Engineering 45(9), 097006 (1 September 2006). https://doi.org/10.1117/1.2354076

Published: 1 September 2006

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