Tetrahedron matching method for detecting scalar volume similarity
Tetrahedron matching method for detecting scalar volume similarity
复制标题
检测标量体积相似度的四面体匹配方法
DOI：
10.3154/jvs.26.supplement1_25
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发表时间：
2006
期刊：
影响因子：
--
通讯作者：
K. Koyamada
中科院分区：
文献类型：
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作者：
Koji Sakai;Tomoki Minami;K. Koyamada
传统的分类和检索系统需要人工输入数据的特殊特征。为了克服这个不希望的任务，一种方法，自动创建和利用“临界点图（CPG）”作为体数据的索引已被提出。为了获得合适的搜索和分类结果，需要从一组选定的体数据中自动计算CPG之间的相似度。我们引入了一个新的特征匹配算法，使两个CPG之间的位置精确对应。该算法是二维指纹匹配中常用的三角形匹配算法的一种扩展。为了评估的有效性，我们评估的数据分辨率和安排在我们提出的基于CPG的方法的影响。我们证实了我们提出的CPG为基础的方法的有效性和实用性时，应用于数值构造的天气体数据集。从计算实验中，我们的新CPG方法已显示出适当的能力，两个不同的体数据之间的相似性计算。
Traditional classifying and searching systems have required special features of data from manual input. To overcome this undesirable task, a method which automatically creates and utilizes a "Critical Point Graph (CPG)" as an index of volume data has been proposed. In order to achieve suitable search and classification results, it is required to automatically calculate similarity between CPGs from a set of selected volume data. We introduce a new feature-matching algorithm to make an exact correspondence of positions between two CPGs. This is an extension of "Triangular Matching Algorithm" which is usually employed in the field of 2D fingerprint matching. In order to evaluate the effectiveness, we evaluated the influence of data resolution and arrangement in our proposed CPG based method. We confirmed the effectiveness and usefulness of our proposed CPG based method when applied to numerically constructed weather volume data sets. From computational experiments, our new CPG method has shown suitable ability for similarity calculation between two dissimilar volume data.