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Global characteristic-based lossless watermarking for 2D-vector maps

机译:基于全局特征的2维矢量地图无损水印

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Due to no damage to original data, the lossless watermarking is more suitable for copyright protection of vector maps. In this paper, a lossless watermarking scheme based on the global characteristics of vector map is proposed. It begins with feature point extraction of each polyline, based on which, for the extracted feature points and non-feature points, the scheme utilizes the relation model established by BP artificial neural network and the singular value decomposition (SVD) to construct the lossless watermarking parameters, respectively. Then through XOR operation between lossless parameters and copyright image, the corresponding detection keys are obtained. This scheme perfectly depicts the global characteristics of each polyline, and has complementary robustness for simplification, compression attacks and geometry attacks, achieves the comprehensive protection purpose of vector maps. Experimental results validate the complementary robustness and effective copyright distinction between different maps of the scheme. In addition, the contradiction between the robustness and imperceptibility in traditional watermarking algorithm is effectively balanced in the scheme without modifying the original vector data, so it is suitable for copyright protection of 2D-vector maps.
机译:由于不会损坏原始数据,因此无损水印更适合矢量地图的版权保护。本文提出了一种基于矢量地图全局特征的无损水印方案。首先从提取每条折线的特征点开始,然后根据提取的特征点和非特征点,利用BP人工神经网络建立的关系模型和奇异值分解(SVD)构造无损水印。参数。然后通过无损参数与版权图像之间的异或运算,获得相应的检测密钥。该方案完美地描绘了每条折线的全局特征,并具有简化,压缩攻击和几何攻击的互补鲁棒性,从而实现了矢量地图的全面保护目的。实验结果验证了该方案不同地图之间的互补性鲁棒性和有效的版权区别。另外,该方案在不修改原始矢量数据的情况下,有效地平衡了传统水印算法的鲁棒性和不可感知性之间的矛盾,因此适合二维矢量图的版权保护。

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