中文摘要：

针对传统图匹配方法的复杂性和图序列化技术对图拓扑结构的敏感性,提出一种基于有序路径集相似性的边界表示模型搜索方法.首先根据模型表面属性将其分类并排序,然后以模型表面作为路径结点分别提取模型的同类表面有序路径集、异类表面有序路径集作为模型的线性表达形式;在此基础上,提出一种基于有序路径间距离的边界表示模型距离度量方法,通过逐级计算有序路径间的距离、有序路径集间的距离,得到模型间的距离.模型搜索实验的结果表明,文中方法对模型拓扑结构的变化具有一定的鲁棒性,搜索精度高于已有方法,同时在线匹配时间具有多项式级的时间复杂度.

英文摘要：

Due to complexity of conventional graph matching and sensitivity of graph seriation to its topology,this paper proposed an approach to B-rep model retrieval based on similarity of ordered paths.At first,facets of the model are sorted by their properties.Then the facets are taken as the nodes of paths,and the facets with same or different property are chosen to form ordered paths of homogeneous or heterogeneous facet respectively,which is taken as a linear representation of B-rep model.Based on this representation,a distance measurement between B-rep models which is calculated from the distance of ordered paths is presented.By calculating distance of two ordered paths and distance of ordered paths sets in a stepwise manner,the distance between B-rep models is determined.The results from searching experimental tests demonstrate that the approach based on ordered paths has robustness against variation in topological structure and the retrieval accuracy is better than that of existing methods.In addition,the time for online matching of this approach is with polynomial-time complexity.