Abstract—Vector geospatial data is of great value, due to the cost processes of acquiring such data. Thus, how to protect vector geospatial data from piracy has become a hot issue in the community of geographic information science, and among which watermarking has been proven a feasible tool. This paper proposes a blind watermarking technique for protecting vector geospatial data from illegal use, mainly taking into consideration four rules in watermarking, i.e. usability, invisibility, robustness, and blindness. The technique consists of two processes: a watermark embedding process and a watermarking extracting process. In the watermarking process, the technique firstly determines two feature layers and selects the key points from each layer as watermark embedding positions; then it shuffles the watermark and embeds the watermark in the two layers, respectively. At the beginning of the watermark extracting process, a step similar to that in the watermarking embedding process is carried out to obtain the two feature layers and the key points that have been used for embedding the watermark; then the coordinates of the key points are checked to extract the embedded watermark from the two feature layers, respectively; finally the similarity degree of the two watermarks extracted from two feature layers is calculated, by which the conclusion on whether the data contains the watermark can be made. Our experiments show that the technique can resist the attacks from data format change, random noise, similarity transformation, and data editing.
Index Terms—Blind Watermarking Technique, Key Point, Similarity Degree, Vector Geospatial Data
Haowen Yan, School of Mathematics, Physics and Software Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China, (e-mail: email@example.com).
Jonathan Li, Department of Geography & Environment Management, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada, (e-mail: Junli@uwaterloo.ca).
Cite: Haowen Yan and Jonathan Li, "A Blind Watermarking Approach to Protecting Geospatial Data from Piracy," International Journal of Information and Education Technology vol. 1, no. 2, pp. 94-98, 2011.