图匹配技术研究

图(Graph)在众多的科学领域和工程领域(如模式识别和计算机视觉)中具有广泛的应用 ,其具备 强大的信息表达能力。当图被用来表示物体结构时,衡量物体的相似程度将会被转化成计算两个图的相似度,这就是图匹配(Graph Matching)。近几十年来,对图匹配相关技术和算法的研究已经成为了研究领域内的一个重要课题,尤其是随着大数据时代的来临,图作为数据之间关系的一种表示形式,将会受到越来越多的关注。文中对图匹配技术的发展现状进行了综述,详细介绍了该技术的理论基础,梳理了解决图匹配问题的几种主流思路。最后,结合图匹配技术的一种具体应用对几种算法的性能进行了对比分析。

Survey of Graph Matching Algorithms

Graph has been applied to many fields of science and technology,such as pattern recognition and computer vision,because of its powerful representation of structure and information .When graph is used to represent object structure,calculating the similarity of two objects equals to calculating the similarity of two graphs.The research of graph matching algorithms has been carried out for decades,especially as the big data technology increasingly becomes hot recently.As a representation of relationship among data,graph has been paid more attention in the research.This paper gave a survey of the development of the graph matching technology as well as the foundation of this theory.Then,this paper made a summarization of graph matching methods,and compared the performance of several classical algorithms.