1.中国科学院南京地理与湖泊研究所,江苏 南京,210008
2.中国科学院流域地理学重点实验室,江苏 南京,210008
3.浙江师范大学地理与环境科学学院,浙江 金华,321004
4.西北大学城市与环境学院,陕西 西安,710127
邱银国,博士,副研究员,主要从事地理信息安全和智慧流域等方面的研究。ygqiu@niglas.ac.cn
收稿:2023-04-15,
纸质出版:2025-01-05
移动端阅览
邱银国,郑皎珏,肖启涛,等.利用差错控制编码构建矢量地图自纠错数字水印模型[J].武汉大学学报(信息科学版),2025,50(1):164-173.
QIU Yinguo,ZHENG Jiaojue,XIAO Qitao,et al.Construct Self-correcting Digital Watermarking Model for Vector Map Based on Error-Control Coding[J].Geomatics and Information Science of Wuhan University,2025,50(1):164-173.
邱银国,郑皎珏,肖启涛,等.利用差错控制编码构建矢量地图自纠错数字水印模型[J].武汉大学学报(信息科学版),2025,50(1):164-173. DOI:10.13203/j.whugis20220419
QIU Yinguo,ZHENG Jiaojue,XIAO Qitao,et al.Construct Self-correcting Digital Watermarking Model for Vector Map Based on Error-Control Coding[J].Geomatics and Information Science of Wuhan University,2025,50(1):164-173. DOI:10.13203/j.whugis20220419
数字水印技术为矢量地图的安全保护提供了新的手段,但已有研究主要聚焦于水印嵌入过程,而水印检测通常仅为水印嵌入的逆过程,缺乏针对水印提取结果的自优化方法,水印检测效果还有很大提升空间。为解决该问题,设计了一种基于版权水印信息差错控制编码的矢量地图自纠错数字水印模型。该模型通过对版权水印信息进行纠错编码和校验编码,并基于无损压缩编码方法在水印信息长度的约束下构造具备自纠错能力的混合水印信息;顾及混合水印信息特征和矢量地图顶点稳定性差异,设计了混合水印信息分类嵌入方法;水印提取后,可通过校验码和纠错码提取结果对版权水印信息提取结果进行误码检测和纠正,进一步提升版权水印检测效果。仿真实验结果表明,所提出的方法可以在已有研究的基础上进一步提升版权水印检测效果,且具有理想的可逆性、不可见性、稳健性和水印容量。
Objectives
2
Digital watermarking technology provides a new means for the security protection of vector map. Existing researches focus mainly on the watermark embedding process
while the watermark detection process is typically the inverse one of the watermark embedding process
and there is a lack of self-optimization methods of watermark extraction results. Consequently
there is still much upgrade space for the watermark detection effect. A self-correcting digital watermarking model is designed for vector map based on error-control coding of copyright watermark information.
Methods
2
Error-correction coding (ECC) and cyclic redundancy checking (CRC) are performed on the original copyright watermark data firstly. The original watermark data and the ECCs and CRC codes are then treated by lossless compression coding
i.e. Huffman coding (HC)
so that the watermark length can be constrained. The mixed watermark data with self-correcting ability is then generated by combining the results of HC. Afterwards
a differentiated embedding method is proposed for the various components of the generated mixed watermark data
conside‑ring their different characteristics and the stability difference of map vertices. After watermark extraction
Huffman decoding (HD) is firstly performed on the extracted results and then the copyright watermark data
the ECC and the CRC codes can be obtained by separation. Afterwards
partial error bits in the obtained copyright watermark data can be detected and corrected based on the obtained ECC and CRC codes
and the detection effect of copyright watermark can be further improved.
Results
2
Experimental results show that the proposed method can improve further the detection effect of copyright watermark based on previous research
and it has ideal reversibility
invisibility
robustness and watermark capacity.
Conclusions
2
Although the constructed digital watermarking model is quite robustness against conventional transformations and attacks
it is very fragile under map scaling. Therefore
it is worthy of further study on the construction of geometric invariants of vector map data
as well as the corresponding watermark embedding methods.
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