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http://dx.doi.org/10.3837/tiis.2019.12.022

High-Capacity and Robust Watermarking Scheme for Small-Scale Vector Data  

Tong, Deyu (College of Information Engineering, Nanjing University of Finance and Economics)
Zhu, Changqing (Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education)
Ren, Na (Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education)
Shi, Wenzhong (Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.13, no.12, 2019 , pp. 6190-6213 More about this Journal
Abstract
For small-scale vector data, restrictions on watermark scheme capacity and robustness limit the use of copyright protection. A watermarking scheme based on robust geometric features and capacity maximization strategy that simultaneously improves capacity and robustness is presented in this paper. The distance ratio and angle of adjacent vertices are chosen as the watermark domain due to their resistance to vertex and geometric attacks. Regarding watermark embedding and extraction, a capacity-improved strategy based on quantization index modulation, which divides more intervals to carry sufficient watermark bits, is proposed. By considering the error tolerance of the vector map and the numerical accuracy, the optimization of the capacity-improved strategy is studied to maximize the embedded watermark bits for each vertex. The experimental results demonstrated that the map distortion caused by watermarks is small and much lower than the map tolerance. Additionally, the proposed scheme can embed a copyright image of 1024 bits into vector data of 150 vertices, which reaches capacity at approximately 14 bits/vertex, and shows prominent robustness against vertex and geometric attacks for small-scale vector data.
Keywords
Digital watermarking; capacity; robustness; vector data; small-scale data;
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