Lossless Watermarking Algorithm for Geographic Point Cloud Data Based on Vertical Stability

Author:

Zhang Mingyang1,Dong Jian12,Ren Na34,Guo Shuitao3

Affiliation:

1. Department of Military Oceanography and Hydrography & Cartography, Dalian Naval Academy, Dalian 116018, China

2. Key Laboratory of Hydrographic Surveying and Mapping of PLA, Dalian Naval Academy, Dalian 116018, China

3. Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China

4. Hunan Engineering Research Center of Geographic Information Security and Application, The Third Surveying and Mapping Institute of Hunan Province, Changsha 410018, China

Abstract

With the increasing demand for high-precision and difficult-to-obtain geospatial point cloud data copyright protection in military, scientific research, and other fields, research on lossless watermarking is receiving more and more attention. However, most of the current geospatial point cloud data watermarking algorithms embed copyright information by modifying vertex coordinate values, which not only damages the data accuracy and quality but may also cause incalculable losses to data users. To maintain data fidelity and protect its copyright, in this paper, we propose a lossless embedded watermarking algorithm based on vertical stability. First, the watermark information is generated based on the binary encoding of the copyright information and the code of the traceability information. Second, the watermark index is calculated based on the length of the watermark information after compression and the vertical distribution characteristics of the data. Finally, watermark embedding is completed by modifying the relative storage order of the corresponding data according to the index and watermark value. The experimental results show that the proposed algorithm has good invisibility without damaging the data accuracy. In addition, compared with existing algorithms, this method has a higher robustness under operations such as projection transformation, precision perturbation, and vertex deletion of geospatial point cloud data.

Funder

National Natural Science Foundation of China

Natural Science Foundation of China

Research Foundation of the Department of Natural Resources of Hunan Province

Publisher

MDPI AG

Subject

Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Geography, Planning and Development

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