《计算机应用研究》|Application Research of Computers

基于粒子群算法的三维CAD模型相似性计算

Similarity calculation of 3D CAD model based on particle swarm algorithm

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作者 高雪瑶,陈育南,张春祥
机构 哈尔滨理工大学 a.计算机科学与技术学院;b.软件与微电子学院,哈尔滨 150080
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文章编号 1001-3695(2019)03-063-0954-03
DOI 10.19734/j.issn.1001-3695.2017.10.1018
摘要 为了更加准确地度量两个模型之间的形状差异,提出了一种基于粒子群的模型相似性计算方法。利用面的组成边数来构造面相似度矩阵,通过粒子群算法对该矩阵进行搜索,得到了两个模型之间的最优面匹配序列。根据这个最优面匹配序列,从面相似度矩阵中提取对应的面相似性值。通过累积面之间的相似性来计算模型之间的整体相似性,以此为基础来度量模型之间的差异。实验结果表明,该方法能够准确地度量两个模型之间的相似程度。
关键词 形状差异;模型相似性;粒子群算法;匹配序列
基金项目 国家自然科学基金资助项目(61502124)
黑龙江省自然科学基金资助项目(F201420)
本文URL http://www.arocmag.com/article/01-2019-03-063.html
英文标题 Similarity calculation of 3D CAD model based on particle swarm algorithm
作者英文名 Gao Xueyao, Chen Yunan, Zhang Chunxiang
机构英文名 a.SchoolofComputerScience&Technology,b.SchoolofSoftware&Microelectronics,HarbinUniversityofScience&Technology,Harbin150080,China
英文摘要 In order to measure shape difference of two models accurately, this paper proposed a method for calculating model similarity based on particle swarm.It used edge number of face to construct face similarity matrix, and used particle swarm algorithm to search this matrix to get an optimal face matching sequence between two models.It extracted correspondent face similarity values according to this face matching sequence from face similarity matrix.This paper accumulated face similarities to calculate two models’ similarity and measured shape difference of two models.Experimental results show that this method can evaluate similarity between two models accurately.
英文关键词 shape difference; model similarity; particle swarm algorithm; matching sequence
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收稿日期 2017/9/29
修回日期 2017/11/17
页码 954-956,960
中图分类号 TP391.7
文献标志码 A