  The advancement in digital technologies have made it possible to produce
perfect copies of digital content. In this environment, malicious users
reproduce the digital content and share it without compensation to the content
owner. Content owners are concerned about the potential loss of revenue and
reputation from piracy, especially when the content is available over the
Internet. Digital watermarking has emerged as a deterrent measure towards such
malicious activities. Several methods have been proposed for copyright
protection and fingerprinting of digital images. However, these methods are not
applicable to text documents as these documents lack rich texture information
which is abundantly available in digital images. In this paper, a framework
(mPDF) is proposed which facilitates the usage of digital image watermarking
algorithms on text documents. The proposed method divides a text document into
texture and non-texture blocks using an energy-based approach. After
classification, a watermark is embedded inside the texture blocks in a content
adaptive manner. The proposed method is integrated with five known image
watermarking methods and its performance is studied in terms of quality and
robustness. Experiments are conducted on documents in 11 different languages.
Experimental results clearly show that the proposed method facilitates the
usage of image watermarking algorithms on text documents and is robust against
attacks such as print & scan, print screen, and skew. Also, the proposed method
overcomes the drawbacks of existing text watermarking methods such as manual
inspection and language dependency.
