A Coded Digital Watermarking Recognition Using Neural Network Method

Abstract:

Digital watermarking is an encryption technology commonly used to protect intellectual property and copyright. Although watermarks possess advantageous secrecy and robustness, environmental interference in the image propagation through the Internet is inevitable and, certainly, human-based image modification can also destroy the watermark. In this study, we restored watermarks that had already been affected by noise interference, used the Walsh-Hadamard codes as the watermark identification codes, and applied salt-and-pepper noise and Gaussian noise to destroy watermarks. First, we used a low-pass filter and median filter to remove noise interferences. Although these filters can suppress noises, watermarked images remain unidentifiable when the noise interferences strongly. Finally, we used a back-propagation neural network algorithm to filter noises, obtaining results that exceeded our expectations. We removed nearly all noise and recovered the originally embedded watermarks of Walsh-Hadmard codes.

• Periodical: Applied Mechanics and Materials (Volumes 284-287)
• Pages: 2961-2964
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.284-287.2961
• Online since: January 2013
• Authors: Chih Ta Yen, Ing Jr Ding, Zong Wei Lai
• Keywords: Back-Propagation Neural Network, Digital Watermark, Gaussian Noise, Salt and Pepper Noise, Walsh-Hadamard Code

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