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	Author	Pau Riba; Josep Llados; Alicia Fornes
	Title	Error-tolerant coarse-to-fine matching model for hierarchical graphs			Type	Conference Article
	Year	2017	Publication	11th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition	Abbreviated Journal
	Volume	10310	Issue		Pages	107-117
	Keywords	Graph matching; Hierarchical graph; Graph-based representation; Coarse-to-fine matching
	Abstract	Graph-based representations are effective tools to capture structural information from visual elements. However, retrieving a query graph from a large database of graphs implies a high computational complexity. Moreover, these representations are very sensitive to noise or small changes. In this work, a novel hierarchical graph representation is designed. Using graph clustering techniques adapted from graph-based social media analysis, we propose to generate a hierarchy able to deal with different levels of abstraction while keeping information about the topology. For the proposed representations, a coarse-to-fine matching method is defined. These approaches are validated using real scenarios such as classification of colour images and handwritten word spotting.
	Address	Anacapri; Italy; May 2017
	Corporate Author				Thesis
	Publisher	Springer International Publishing	Place of Publication		Editor	Pasquale Foggia; Cheng-Lin Liu; Mario Vento
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	GbRPR
	Notes	DAG; 600.097; 601.302; 600.121			Approved	no
	Call Number	Admin @ si @ RLF2017a			Serial	2951
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