...
首页> 外文期刊>Multimedia Tools and Applications >Polyline curvatures based robust vector data hashing
【24h】

Polyline curvatures based robust vector data hashing

机译:基于折线曲率的鲁棒矢量数据哈希

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

The growth in applications for vector data such as CAD design drawings and GIS digital maps has increased the requirements for authentication, copy detection, and retrieval of vector data. Vector data hashing is one of the main techniques for meeting these requirements. Its design must be robust, secure, and unique, which is similar to image or video hashing. This paper presents a vector data hashing method based on the polyline curvature for design drawings and digital maps. Our hashing method extracts the feature values by projecting the polyline curvatures, which are obtained from groups of vector data using GMM clustering, onto random values, before generating the final binary hash by binarization. A robustness evaluation showed that our hashing method had a very low false detection probability during geometrical modifications, rearrangements, and similar transformations of objects and layers. A security evaluation based on differential entropy showed that the level of uncertainty was very high with our hashing method. Furthermore, a uniqueness evaluation showed that the Hamming distances between hashes were very low.
机译:矢量数据(例如CAD设计图和GIS数字地图)的应用程序的增长,增加了对身份验证,复制检测和矢量数据检索的要求。矢量数据哈希是满足这些要求的主要技术之一。它的设计必须健壮,安全且独特,这类似于图像或视频哈希。本文提出了一种基于折线曲率的矢量数据散列方法,用于设计图和数字地图。我们的散列方法通过在通过二值化生成最终的二进制散列之前,通过将使用GMM聚类从矢量数据组中获得的折线曲率投影到随机值上来提取特征值。鲁棒性评估表明,在对象和图层的几何修改,重排以及类似的转换过程中,我们的哈希方法具有极低的错误检测概率。基于微分熵的安全性评估表明,使用我们的哈希方法时,不确定性级别很高。此外,唯一性评估表明,哈希之间的汉明距离非常低。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号