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一种采用曲线分割的矢量图水印算法 被引量:9

A Watermarking Algorithm for Vector Graphics Using Curve Partition
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摘要 针对矢量图形既需具有鲁棒性又要保证图形几何精度的问题,提出了一种针对矢量图形水印嵌入、提取和检测方法。水印的嵌入算法是将一幅矢量图形视为曲线的集合,按设定阈值进行曲线分割;再在容差范围内,使每条曲线对应一个水印位,且对曲线中每个结点嵌入一个含有用户证书信息的水印点。水印提取算法则对原图和含水印图进行对应的分割;按嵌入算法的逆过程逐曲线提取出水印信息;再通过计算原水印信息和所提取水印信息的相似度检测水印存在与否和符合程度。实验结果表明,该方法在无攻击和几何变形操作攻击下的水印检测相似度均接近1.00;且水印图即使在剪裁了的2/3后,仍能保证大于0.9的相似度;同时,方法具有抗D-P压缩能力,并可借助所给出的相似度阈值经验曲线,控制水印点的偏离角度,或在水印信息检测的自动化处理流程中设定参数,起到既能保证矢量图形的精度,又具有较好的鲁棒性的作用。 This paper discusses a watermarking method towards keeping robustness and high accuracy of vector graphics. The graphics is treats as a set of curves in the embedding algorithm, and each curve is divided into several shorter curves under a given threshold. And then a watermark bit combined with user certificate is embedded into each segment around the node for every cutting curve. To extract the watermark, it also divides up the watermarked graphics according to the division of the original graphics. Then, it extracts the watermark bit from each curve with the inverse procedure of the embedding process. Finally, the method calculates the similarity between the original watermark bits and the extracted ones from the watermarked graphics, and determines whether the watermark exists or not. The experiment results showed that the method not only guarantees the accuracy of vector graphics but also prossesses good robustness, such as it gives 1.00 similarities under no attack or only geometric transformation with the map; the anti-cropping ability gives 0. 9 even for the graphics cropped 2/3. And it also has the ability of anti-compression of D-P approach and the experiment curve of the similarity threshold given which helps to control the antiattack ability of watermark and set parameters for an automatic procedure of watermark detection.
出处 《中国图象图形学报》 CSCD 北大核心 2009年第8期1516-1522,共7页 Journal of Image and Graphics
基金 国家自然科学基金项目(60842007) 广东省百项工程项目(2002B32101) 广东省重点引导项目(2004B32501001 2005B30801006)
关键词 矢量图形 数字水印 鲁棒性 相似度 曲线分割 vector graphics, digital watermark, robustness, similarity, curve partition
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参考文献11

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二级参考文献34

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