Content-based Retrieval of 3D CAD Subassemblies Using 3D Radon Transform

Q4 Computer Science
Kaoru Katayama, Youta Yamaji, Shotaro Toyoizumi, Takashi Hirashima
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引用次数: 0

Abstract

We propose a content-based method for retrieving the 3D CAD assemblies which contain or are contained in the assembly given as a query from a database. The retrieval is based on ranking assemblies in the database according to their content rates which are different criteria from the similarities of shapes. The content rate is computed by comparing the projections of components constituting an assembly in the database with those of components constituting the query. We use the 3D Radon transform to obtain the projections. In existing methods for retrieving CAD models, projections of each model onto 2D planes, which are a set of two-dimensional data, are often used to compute the similarity between them. The proposed method simplifies the process of comparing the projections of components because the projections using the 3D Radon transform are a set of one-dimensional data. The method has the unique feature of identifying the component layouts, which reflect the technical know-how and information of the product designers. The components which have the same shapes but different properties such as material names are also distinguished based on their layouts without depending on the labels assigned to the properties. Other than our previous method, no existing methods possess such features. We show that the proposed method has better performance in the retrieval precision and processing time than the previous method.
基于内容的三维CAD子组件三维Radon变换检索
我们提出了一种基于内容的方法,用于从数据库中检索包含或包含在给定装配中的3D CAD装配。检索是基于数据库中组件的排序,根据它们的内容率,这是不同于形状相似性的标准。通过比较数据库中构成组件的组件的投影与构成查询的组件的投影来计算内容率。我们使用3D Radon变换来获得投影。在现有的CAD模型检索方法中,通常使用每个模型在二维平面上的投影(即一组二维数据)来计算它们之间的相似度。由于利用三维Radon变换得到的投影是一组一维数据,因此该方法简化了构件投影比较的过程。该方法具有识别部件布局的独特特点,反映了产品设计者的技术知识和信息。具有相同形状但不同属性(如材质名称)的组件也可以根据其布局进行区分,而不依赖于分配给属性的标签。除了我们之前的方法,没有其他方法具有这些特征。结果表明,该方法在检索精度和处理时间上均优于传统方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Information Processing
Journal of Information Processing Computer Science-Computer Science (all)
CiteScore
1.20
自引率
0.00%
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