Document Images Watermarking For Security Issue Using Fully Convolutional Networks

In the literature, the watermarking schemes for document images in spatial domain mainly focus on text content, so they need to be further improved to be possibly applied on general content. In this paper, we propose a blindly invisible watermarking approach for security matter of general grayscale documents. In order to detect stable regions used for hiding secret data, we make the best use of fully convolutional networks (FCN). The FCN for the problem of document structure segmentation is adjusted to solve the problem of watermarking regions detection wherein we consider various types of segmented content regions having the same label. The segmented content regions are then known as watermarking regions. Next, the watermarking pattern is constructed with the aim of detecting potential positions where the watermarking process is carried out. Lastly, the watermarking algorithm is developed by dividing gray level values pertaining to each watermarking pattern into two groups for carrying one watermark bit. The experiments are performed on various document contents, and our approach obtains high performance in terms of imperceptibility, capacity and robustness against distortions caused by JPEG compression, geometric transformation and print-and-scan process.