Print to Scan Resistant Watermarking based on Green Noise Diffusion Method using Machine Learning

The green-noise diffused watermarking method is resistant to printing and scanning, and the embedded pattern is not easily visible. We extended this method to enable the extraction of watermark information from cropped images by embedding marker patterns. We used machine learning and embedded five g...

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Bibliographic Details
Published in2022 24th International Conference on Advanced Communication Technology (ICACT) pp. 307 - 312
Main Authors Cho, Yoshi Michael, Imada, Hiroyuki, Kawamura, Naoto, Kang, Hyunho, Iwamura, Keiichi
Format Conference Proceeding
LanguageEnglish
Published Global IT Research Institute - GiRI 13.02.2022
Subjects
Codes
Communications technology
Copyright Protection
Data Hiding
Machine learning
Printing
Resistance
Synchronization
Watermarking
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Summary:The green-noise diffused watermarking method is resistant to printing and scanning, and the embedded pattern is not easily visible. We extended this method to enable the extraction of watermark information from cropped images by embedding marker patterns. We used machine learning and embedded five green-noise patterns, including four value patterns and one marker pattern. Correct watermark extraction rate of over 95% are obtained from the printed images. We also embedded sub-information in the marker pattern to obtain block synchronization from the cropped images. Furthermore, the introduction of RS codes allowed us to obtain an extraction correctness rate close to 100% from both electronic and printed images.
ISSN:1738-9445
DOI:10.23919/ICACT53585.2022.9728895