# A High Capacity Watermarking Technique for the Printed Document
## 1 Introduction  
With the development of the Internet, data and information are ubiquitous in our daily life, and information exchange is becoming more frequent. However, digital information is easy to copy and transcribe, the copyright protection of digital information is becoming ever more prominent. Digital watermarking technology provides a way to solve the appeal problem. At present, the digital watermarking technology is relatively mature for images because they have a lot of redundant information to embed watermark, and these algorithms usually use the information in frequency domain of image for watermark embedding. For example, literature [1; 2; 3; 4] embeds watermark information in the discrete wavelet transform (DWT) domain of image and achieve good results. But the text document has relatively little redundant information, so how to effectively add digital watermark to the document is relatively difficult [5]. In addition, a text file not only appears in the form of digital information, but also in paper status by printing, copying, etc. Therefore, it is essential to study the anti-print scan text watermark for copyright protection [6]. The digital watermark is embedded with the redundant carrier of the text, and it is supposed to have better robustness, good visual effects and huge watermark capacity. Therefore, we need to make a tradeoff amongst the three to achieve better results. In general, the current text watermarkingalgorithms can be divided into three categories [7; 8]: One is based on the text structure, another is based on the natural language processing, and the third is based on the image processing. The text structure-based methods embed the watermark information by adjusting some features of text, such as line spacing, word spacing, and punctuation position. [PERSON] et al. proposed a method of line-shift coding [9] and word-shift coding [10]. Line spacing is used to embed watermark information in line-shift coding. Word-shift coding uses the word spacing to embed watermark information. They are both anti-print scan algorithms. However, these methods cannot resist the influence of text format changes, and the watermark capacity is relatively small. Many scholars are likewise constantly researching the algorithm of this type. For example, [PERSON] et al. [11] use line-shift coding and word-shift coding to embed watermark information together, and add error correction technology to resist attacks. Linguistic-based approaches use the semantic features of the text to embed a watermark. For example, by replacing certain words or sentences in the text to embed the watermark without touching the semantics of the text content. [PERSON] et al. [12; 13] studied the text watermarking algorithm based on semantic features. This type of method will change the text content, so it does not applicable to the cases where the text content cannot be changed. The following research [14] is a good review article which presents a comparative analysis of structural and linguistic method, and some guidelines and directions are proposed in this paper. Image-based methods need to convert the text documents into images, and embed the watermark by processing the features in the image. According to the different features used, the current image-based methods can be roughly divided into several types: based on shape features, gray-based features, boundary-based features, pixel-based features, and shading-based features. Table 1 shows the analysis and comparison of several algorithms. In summary, existing text watermarking algorithms have different spaces for improvement in watermark capacity, visual effects, robustness, and blind extraction. Therefore, this paper proposes a text watermarking algorithm that is resistant to print-scan and can embed information at large capacities. The algorithm combines the print-scan invariant, Fourier boundary descriptors, quadratic quantization function, and the QR code, etc.