平面细分中精确模式匹配的线性算法

Pedro Ribeiro de Andrade Neto, A. Guedes
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引用次数: 0

摘要

图子同构是解决模式搜索问题的一种非常常用的方法,但这是一个np完全问题。这样,就有必要投入研究近似解,或在问题的特殊情况下。平面细分可以被认为是图的一种特殊情况,因为除了节点和边之外,还有一个与边的顺序相关的更严格的拓扑结构,这就产生了面的概念。本文提出了一种平面细分中模式搜索的线性算法。该算法基于对偶图和区域邻接图(RAG)的混合方法来表示模式,节省了任何额外的存储成本。因此,使用区域增长算法在搜索细分中查看模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Linear Algorithm for Exact Pattern Matching in Planar Subdivisions
Graph sub-isomorphism is a very common approach to solving pattern search problems, but this is a NP-complete problem. This way, it is necessary to invest in research of approximate solutions, or in special cases of the problem. Planar subdivisions can be considered as a special case of graphs, because, in addition to nodes and edges, there is a more rigid topology in relation to the order of the edges, arising to the concept of face. This work presents a linear algorithm for pattern search in planar subdivisions. The presented algorithm is based on a hybrid approach between the dual and the region adjacency graph (RAG) to represent the patterns, saving any additional storage cost. Thus, the patterns are looked over the search subdivision, using a region growing algorithm.
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