A zero-watermarking algorithm for vector geographic data based on feature invariants

Wang, Shuai; Zhang, Liming; Zhang, Qihang; Liu, Yu

doi:10.1007/s12145-022-00886-5

Cited by 8 publications

(3 citation statements)

References 26 publications

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“…Many research used deliberate interference reduction strategies, but the quality and availability of watermarked vector maps are still affected to varying degrees. In this case, the zero-watermarking algorithm with lossless characteristics has attracted more and more attention [ 20 , 23 , 24 , 25 ].…”

Section: Related Workmentioning

confidence: 99%

Zero-Watermarking for Vector Maps Combining Spatial and Frequency Domain Based on Constrained Delaunay Triangulation Network and Discrete Fourier Transform

Chen

et al. 2023

Entropy

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With its lossless properties, zero-watermarking has attracted a lot of attention in the field of copyright protection for vector maps. However, the common zero-watermarking algorithm puts too much emphasis on mining for global features, making it vulnerable to cropping attacks, and the robustness is not comprehensive enough. This study provides a vector map zero-watermarking scheme that utilizes spatial statistical information and frequency domain transformation methods in an effort to solve the aforementioned issue. In order to make the scheme more resistant to cropping and compression, it is constructed on the basis of feature point extraction and point constraint blocking of the original vector map. Within each sub-block, feature points are used to build constraint Delaunay triangulation networks (CDTN), and the angular values within the triangle networks are then extracted as spatial statistics. The angle value sequence is further transformed by discrete Fourier transform (DFT), and the binarized phase sequence is used as the final feature information to build a zero watermark by executing an exclusive disjunction operation with the encrypted copyright watermark image, both of which contribute to the scheme’s robustness and security. The results of the attack experiments show that the proposed vector map zero-watermarking can restore identifiable copyright images under common geometric attacks, cropping attacks, and coordinate system transformations, demonstrating a high level of robustness. The theoretical basis for the robustness of this watermarking scheme is the stability of CDTN and the geometric invariance of DFT coefficients, and both theory and experiment validate the method’s validity.

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Section: Related Workmentioning

confidence: 99%

Zero-Watermarking for Vector Maps Combining Spatial and Frequency Domain Based on Constrained Delaunay Triangulation Network and Discrete Fourier Transform

Chen

et al. 2023

Entropy

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“…Digital watermarking technology is considered an effective solution for protecting the copyright of 3D models (Pham et al 2018;Lee et al 2023). In the research of geospatial data security, digital watermarking technology has been primarily applied to vector geographic data (Hou et al 2018;Zhu et al 2021;Wang et al 2023;Ren et al 2020) and remote sensing image (Qin et al 2021;Fares et al 2020;Tong et al 2019). However, the research on data protection methods for 3D models is still in its early stages.…”

Section: Introductionmentioning

confidence: 99%

Precision Controllable Reversible Watermarking Algorithm for Oblique Photography 3D Models

Wang,

Zhang,

Zhang

et al. 2023

Preprint

Self Cite

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The existing reversible watermarking algorithms for the oblique photography 3D model can only restore the original model or not, which fails to meet the diverse needs of different users. Therefore, we propose a reversible watermarking algorithm for the oblique photography 3D model in this paper, aiming to achieve controlled model error recovery. Firstly, according to its global stability, the feature points of the oblique photography 3D model are extracted by utilizing the mean angle between vertex normals. Secondly, a mapping relationship is established based on the ratio of distances between feature points and non-feature points. Then, the vertices are grouped, with each group consisting of one feature point corresponding to several non-feature points. Finally, a spherical coordinate system is constructed with the feature point as the origin of each group. The watermark information is embedded by modifying the radius of the coordinate system. In the process of extracting the watermark, we extracted the watermark from different positions within the radius. This method recovers the model by obtaining different radii so that the method can achieve controlled data error. In addition, the experimental results have demonstrated that this algorithm can achieve controlled recovery of model error and exhibits good robustness against attacks such as translation, rotation, cropping, and simplification.

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“…The application prospects of digital watermarking technology in securing vector geographic data are highly significant. Numerous scholars have extensively investigated digital watermarking technology for vector geographic data, yielding a plethora of valuable research findings [1][2][3][4][5][6][7][8][9][10][11]. The current research on digital watermarking technology for vector geographic data primarily focuses on robust and fragile watermarking techniques, which are predominantly employed to address issues related to data copyright protection, single-user usage tracking, and content authentication.…”

Section: Introductionmentioning

confidence: 99%

Multiple Watermarking Algorithms for Vector Geographic Data Based on Multiple Quantization Index Modulation

Wang,

Yang,

Ding

2023

Applied Sciences

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Multiple digital watermarking is an important and challenging task in geographic information science and data security. Vector geographic data are a basic data format for digital geographic data storage, and the security protection of these data involves copyright protection and tracking. As part of the solution, existing digital watermarking algorithms have made contributions to vector geographic data protection. However, when vector geographic data flow through multiple units, they need to be marked to ensure that the original data are not destroyed during data processing. Existing single or multiple data watermarking algorithms often fail in the presence of data processing because the new watermarks overlay the old ones. Consequently, a multiple digital watermarking algorithm based on multiple QIM (quantization index modulation) is proposed. First, based on traditional quantization index modulation (QIM), a multiple QIM is proposed. Unlike traditional QIM, in multiple QIM, the process of quantization is executed multiple times depending on the number of watermarks. Then, the vertices are quantized into different quantization intervals according to the multiple QIM. Finally, multiple watermarks are embedded into different quantization intervals to reduce the interference among multiple watermarks, and the original watermarks are not needed in the process of watermark detection. We then conducted experiments to test the multiple watermark method’s robustness and capacity, with an emphasis on datasets with a lower data volume. The experimental results show that the proposed algorithm achieves good performance in terms of its robustness against common issues, such as vertices addition, data simplification, data cropping, and feature deletion; this holds true for both normal and small amounts of data. Additionally, it has a high multiple watermark capacity.

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A zero-watermarking algorithm for vector geographic data based on feature invariants

Cited by 8 publications

References 26 publications

Zero-Watermarking for Vector Maps Combining Spatial and Frequency Domain Based on Constrained Delaunay Triangulation Network and Discrete Fourier Transform

Zero-Watermarking for Vector Maps Combining Spatial and Frequency Domain Based on Constrained Delaunay Triangulation Network and Discrete Fourier Transform

Precision Controllable Reversible Watermarking Algorithm for Oblique Photography 3D Models

Multiple Watermarking Algorithms for Vector Geographic Data Based on Multiple Quantization Index Modulation

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