Intelligent Extraction of a Digital Watermark from a Distorted Image
Asifullah Khan, Shafaat Tahir, Tae‐Sun Choi · IEICE Transactions on Information and Systems · 2008
We present a novel approach to developing Machine Learning (ML) based decoding models for extracting a watermark in the presence of attacks. Statistical characterization of the components of various frequency bands is exploited to allow blind extraction of the watermark. Experimental results show that the proposed ML based decoding scheme can adapt to suit the watermark application by learning the alterations in the feature space incurred by the attack employed.