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.