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纸质出版日期： 2024-07-16 ，
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奚旭， 瞿成意， 侯渲， 杜景龙. 2024. 运用混合域比值不变性的矢量地图水印算法. 中国图象图形学报， 29(07):2075-2086
Xi Xu， Qu Chengyi， Hou Xuan， Du Jinglong. 2024. Vector map watermarking utilizing the ratio invariance of hybrid domain. Journal of Image and Graphics， 29(07):2075-2086
目的
2
传统基于频率域的矢量地图水印算法往往通过直接修改变换系数实现水印嵌入，嵌入位置随机，且嵌入强度难以控制，实用能力受限。为此，本文挖掘了离散小波变换（discrete wavelet transform，DWT）和复数奇异值分解（complex singular value decomposition，CSVD）系数比值作为新的水印嵌入域，融合系数放大法和量化索引调制（quantization index modulation，QIM）提出了一种嵌入强度可控的鲁棒性矢量地图水印算法。
方法
2
利用道格拉斯—普克算法提取矢量地图特征点，并基于特征点构建复数序列，对复数序列进行二层DWT，得到二层低频系数和二层高频系数。在此基础上，利用CSVD分别计算二层低频和高频系数的奇异值，并以奇异值比值作为水印嵌入域。在水印嵌入阶段，对系数比值放大合适倍数，通过调制放大后的奇异值比值来控制水印嵌入误差，并实现水印信息的盲提取。
结果
2
与最新的3种方法进行比较，本文算法从平移、旋转和缩放的组合攻击中提取的水印图像的归一化相关性系数（normalized correlation，NC）值从低于0.6提升至1。此外，在裁剪、简化和几何攻击的任意组合攻击中，本文算法均能够提取出NC值为1的水印图像，相较于对比方法，鲁棒性更加全面。在不可见性方面，本文算法表现优势，水印嵌入造成的误差被控制在毫米级。
结论
2
本文所提的矢量地图水印算法挖掘了多重频率域变换的比值作为水印嵌入域，具有良好的安全性和稳健性，可以为矢量地图的版权保护提供技术参考。
Objective
2
Traditional frequency domain-based vector map watermarking algorithms often embed watermarks by directly modifying transform coefficients， resulting in limited practicality due to unpredictable embedding locations and difficult-to-control embedding strengths. To address this issue， this paper explores the ratio of coefficients between discrete wavelet transform （DWT） and complex singular value decomposition （CSVD） as a new watermark embedding domain and proposes a robust vector map watermarking algorithm with controllable embedding strength by integrating coefficient amplification and quantization index modulation （QIM）. Through the development of watermark embedding domain mining and watermark embedding method， the overall performance of the frequency domain watermarking for vector maps is enhanced， hence improving the practical utility of watermarking in vector maps.
Method
2
In the process of data preprocessing， the watermarking scheme uses the Douglas-Peucker algorithm to extract feature points from the vector map and constructs a complex sequence based on the feature points. The complex sequence is then subjected to a two-level DWT to obtain low-frequency coefficients （AC2） and high-frequency coefficients （DC2）. On the basis of this approach， the singular values of AC2 and DC2 are calculated using CSVD， and the ratio of singular values is used as the watermark embedding domain. Theoretical analysis determined that the ratio can remain unaffected by geometric transformations of rotation， translation， and scaling， and has a high degree of robustness； likewise， the singular value is relatively stable and insensitive to changes in a few coordinate points. In the watermark embedding stage， the coefficient ratio is appropriately amplified （the amplified coefficient is 10
6
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in this study）， and the QIM method （the interval step size in QIM is set as 10 in this study） is used to modulate the amplified ratio of singular values to control the embedding error and achieve blind extraction of watermark information.
Result
2
We compared the proposed watermarking with three state-of-the-art saliency schemes， namely， DWT-CSVD mixed watermarking algorithm， single wate
rmarking algorithm based on DWT， and the mixed watermarking algorithm based on discrete Fourier-transform frequency domain and spatial domain. After watermark information is embedded into various datasets with different watermarking algorithms， watermarked datasets are subjected to different degrees of geometric attacks， coordinate point attacks， clipping attacks， and combination attacks， and watermark information are extracted under various attack modes. Experimental results show that the proposed algorithm has good invisibility and comprehensive robustness. The difference between the original datasets and the watermarked datasets is difficult to perceive with the naked eye， and the greatest coordinate disturbance induced by watermark embedding is less than 3.92 × 10
-3
， indicating a solid error control effect. Under various degrees of common geometric attacks， cropping， simplification， and coordinate point editing， the proposed watermarking algorithm can always extract the watermark images with an NC value of 1. Even under multiple attack modes involving multiple random combinations， the proposed algorithm is able to extract clearly identifiable watermark images. With the traditional frequency domain vector map watermarking approach， achieving such high performance would be challenging.
Conclusion
2
The proposed vector map watermarking algorithm exploits the ratio of multiple frequency transforms as the watermark embedding domain， which is secure and robust and can provide a technical reference for copyright protection of vector maps.
离散小波变换（DWT）复数奇异值分解（CSVD）嵌入域数字水印矢量地图
discrete wavelet transform （DWT）complex singular value decomposition （CSVD）embedding domaindigital watermarkingvector map
Abubahia A and Cocea M. 2017. Advancements in GIS map copyright protection schemes — a critical review. Multimedia Tools and Applications， 76（10）： 12205-12231 ［DOI： 10.1007/s11042-016-3441-zhttp://dx.doi.org/10.1007/s11042-016-3441-z］
Cox G S and de Jager G. 1992. A survey of point pattern matching techniques and a new approach to point pattern recognition//Proceedings of 1992 South African Symposium on Communications and Signal Processing. Cape Town， South Africa： IEEE： 243-248 ［DOI： 10.1109/COMSIG.1992.274276http://dx.doi.org/10.1109/COMSIG.1992.274276］
Erfani Y， Pichevar R and Rouat J. 2017. Audio watermarking using spikegram and a two-dictionary approach. IEEE Transactions on Information Forensics and Security， 12（4）： 840-852 ［DOI： 10.1109/TIFS.2016.2636094http://dx.doi.org/10.1109/TIFS.2016.2636094］
Gaata M T. 2018. Robust watermarking scheme for GIS vector maps. Ibn AL-Haitham Journal for Pure and Applied Sciences， 31（1）： 277-284 ［DOI： 10.30526/31.1.1835http://dx.doi.org/10.30526/31.1.1835］
Li Y Y and Xu L P. 2004. Vector graphical objects watermarking scheme in wavelet domain. Acta Photonica Sinica， 33（1）： 97-100
李媛媛， 许录平. 2004. 矢量图形中基于小波变换的盲水印算法. 光子学报， 33（1）： 97-100
Lyu W Q and Zhang L M. 2018. A DFT-based zero-watermarking agorithm for vector geodata. Journal of Geomatics Science and Technology， 35（1）： 94-98， 104
吕文清， 张黎明. 2018. 运用DFT的矢量地理数据零水印算法. 测绘科学技术学报， 35（1）： 94-98， 104 ［DOI： 10.3969/j.issn.1673-6338.2018.01.018http://dx.doi.org/10.3969/j.issn.1673-6338.2018.01.018］
Neyman S N， Pradnyana I N P and Sitohang B. 2014. A new copyright protection for vector map using FFT-based watermarking. Telkomnika， 12（2）： 367-378 ［DOI： 10.12928/telkomnika.v12i2.49http://dx.doi.org/10.12928/telkomnika.v12i2.49］
Peng F， Lei Y Z and Sun X M. 2011. Reversible watermarking algorithm in wavelet domain for 2D CAD engineering graphics. Journal of Image and Graphics， 16（7）： 1134-1139
彭飞， 雷瑜洲， 孙星明. 2011. 2维CAD工程图小波域可逆水印. 中国图象图形学报， 16（7）： 1134-1139 ［DOI： 10.11834/jig.20110720http://dx.doi.org/10.11834/jig.20110720］
Peng Y W， Lan H， Yue M L and Xue Y. 2018. Multipurpose watermarking for vector map protection and authentication. Multimedia Tools and Applications， 77（6）： 7239-7259 ［DOI： 10.1007/s11042-017-4631-zhttp://dx.doi.org/10.1007/s11042-017-4631-z］
Qu C Y， Xi X， Du J L and Wu T. 2022. Robust watermarking scheme for vector geographic data based on the ratio invariance of DWT-CSVD coefficients. ISPRS International Journal of Geo-Information， 11（12）： #583 ［DOI： 10.3390/ijgi11120583http://dx.doi.org/10.3390/ijgi11120583］
Ren N， Guo S T， Zhu C Q and Hu Y C. 2023. A zero-watermarking scheme based on spatial topological relations for vector dataset. Expert Systems with Applications， 226： #120217 ［DOI： 10.1016/j.eswa.2023.120217http://dx.doi.org/10.1016/j.eswa.2023.120217］
Ren N， Tong D Y， Cui H C， Zhu C Q and Zhou Q F. 2022. Congruence and geometric feature-based commutative encryption-watermarking method for vector maps. Computers and Geosciences， 159： #105009 ［DOI： 10.1016/j.cageo.2021.105009http://dx.doi.org/10.1016/j.cageo.2021.105009］
Ren N， Zhao Y Z， Zhu C Q， Zhou Q F and Xu D J. 2021. Copyright protection based on zero watermarking and blockchain for vector maps. ISPRS International Journal of Geo-Information， 10（5）： #294 ［DOI： 10.3390/ijgi10050294http://dx.doi.org/10.3390/ijgi10050294］
Shang Z W， Ren H E and Zhang J. 2008. A block location scrambling algorithm of digital image based on Arnold transformation//Proceedings of the 9th International Conference for Young Computer Scientists. Hunan， China： IEEE： 2942-2947 ［ DOI： 10.1109/ICYCS.2008.99http://dx.doi.org/10.1109/ICYCS.2008.99］
Tong D Y， Zhu C Q and Ren N. 2018. Watermarking algorithm applying to small amount of vector geographical data. Acta Geodaetica et Cartographica Sinica， 47（11）： 1518-1525
佟德宇， 朱长青， 任娜. 2018. 小数据量矢量地理数据水印算法. 测绘学报， 47（11）： 1518-1525 ［DOI： 10.11947/j.AGCS.2018.20170741http://dx.doi.org/10.11947/j.AGCS.2018.20170741］
Wang S， Zhang L M， Li Y， Qin R Z and Zhang Q H. 2022. A zero watermarking algorithm of vector geographic data using singular value decomposition. Science of Surveying and Mapping， 47（11）： 196-203， 222
王帅， 张黎明， 李玉， 秦如贞， 张启航. 2022. 运用奇异值分解的矢量地理数据零水印算法. 测绘科学， 47（11）： 196-203， 222 ［DOI： 10.16251/j.cnki.1009-2307.2022.11.024http://dx.doi.org/10.16251/j.cnki.1009-2307.2022.11.024］
Xi X， Zhang X C， Bao J T and Zhang Y Z. 2022. Watermarking algorithm for vector maps based on improved DFT and QR code. Science of Surveying and Mapping， 47（10）： 190-197
奚旭， 张新长， 鲍建腾， 张亚洲. 2022. 一种改进DFT和QR码的矢量地图数字水印算法. 测绘科学， 47（10）： 190-197 ［DOI： 10.16251/j.cnki.1009-2307.2022.10.025http://dx.doi.org/10.16251/j.cnki.1009-2307.2022.10.025］
Xiao Z J， Zhang H， Chen H and Gao T. 2017. Zero-watermarking based on boost normed singular value decomposition and cellular neural network. Journal of Image and Graphics， 22（3）： 288-296
肖振久， 张晗， 陈虹， 高婷. 2017. 增强奇异值分解和细胞神经网络的零水印. 中国图象图形学报， 22（3）： 288-296 ［DOI： 10.11834/jig.20170302http://dx.doi.org/10.11834/jig.20170302］
Xu D H and Wang Q S. 2010. The study of watermarking algorithm for vector geospatial data based on the phase of DFT//Proceedings of 2010 IEEE International Conference on Wireless Communications， Networking and Information Security. Beijing， China： IEEE： 625-629 ［DOI： 10.1109/WCINS.2010.5541855http://dx.doi.org/10.1109/WCINS.2010.5541855］
Zhang L M， Yan H W and Lyu W Q. 2017. A blind watermarking algorithm robust to projection attacks for vector data. Remote Sensing Information， 32（1）： 175-180
张黎明， 闫浩文， 吕文清. 2017. 一种抗投影攻击的矢量空间数据盲水印算法. 遥感信息， 32（1）： 175-180 ［DOI： 10.3969/j.issn.1000-3177.2017.01.029http://dx.doi.org/10.3969/j.issn.1000-3177.2017.01.029］
Zhang L M， Yan H W， Qi J X and Zhang Y Z. 2016. Feature points based blind watermarking approach for vector data. Science of Surveying and Mapping， 41（4）： 184-189
张黎明， 闫浩文， 齐建勋， 张永忠. 2016. 运用特征点的矢量空间数据盲水印算法. 测绘科学， 41（4）： 184-189 ［DOI： 10.16251/j.cnki.1009-2307.2016.04.036http://dx.doi.org/10.16251/j.cnki.1009-2307.2016.04.036］
Zhang L M， Yan H W， Zhu R and Du P. 2020. Combinational spatial and frequency domains watermarking for 2D vector maps. Multimedia Tools and Applications， 79（41）： 31375-31387. ［DOI： 10.1007/s11042-020-09573-3http://dx.doi.org/10.1007/s11042-020-09573-3］
Zhang Y Q and Wang Q P. 2010. Complementary watermarking algorithm of vector map based on discrete wavelet transform. Journal of Computer Applications， 30（S2）： 110-111， 115
张艳群， 王潜平. 2010. 基于离散小波变换的互补矢量地图数字水印算法. 计算机应用， 30（S2）： 110-111， 115
Zhou C H， Sun J L， Su F Z， Yang X M， Pei T， Ge Y， Yang Y P， Zhang A， Liao X H， Lu F， Gao X and Fu D J. 2020. Geographic information science development and technological application. Acta Geographica Sinica， 75（12）： 2593-2609
周成虎， 孙九林， 苏奋振， 杨晓梅， 裴韬， 葛咏， 杨雅萍， 张岸， 廖小罕， 陆锋， 高星， 付东杰. 2020. 地理信息科学发展与技术应用. 地理学报， 75（12）： 2593-2609 ［DOI： 10.11821/dlxb202012004http://dx.doi.org/10.11821/dlxb202012004］
Zhu C Q. 2017. Research progresses in digital watermarking and encryption control for geographical data. Acta Geodaetica et Cartographica Sinica， 46（10）： 1609-1619
朱长青. 2017. 地理数据数字水印和加密控制技术研究进展. 测绘学报， 46（10）： 1609-1619 ［DOI： 10.11947/j.AGCS.2017.20170301http://dx.doi.org/10.11947/j.AGCS.2017.20170301］
Zhu C Q， Ren N and Xu D J. 2022. Geo-information security technology： progress and prospects. Acta Geodaetica et Cartographica Sinica， 51（6）： 1017-1028
朱长青， 任娜， 徐鼎捷. 2022. 地理信息安全技术研究进展与展望. 测绘学报， 51（6）： 1017-1028 ［DOI： 10.11947/j.AGCS.2022.20220172http://dx.doi.org/10.11947/j.AGCS.2022.20220172］
Zope-Chaudhari S， Venkatachalam P and Buddhiraju K M. 2017. Copyright protection of vector data using vector watermark//Proceedings of 2017 IEEE International Geoscience and Remote Sensing Symposium. Fort Worth， USA： IEEE： 6110-6113 ［DOI： 10.1109/IGARSS.2017.8128403http://dx.doi.org/10.1109/IGARSS.2017.8128403］
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