Image Categorization: Graph Edit Distance Plus Edge Direction Histogram

Gao, X; Xiao, B; Tao, D; Li, X

Image Categorization: Graph Edit Distance Plus Edge Direction Histogram

Gao, X Xiao, B Tao, D

Li, X

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Publisher:: Pergamon-elsevier Science Ltd
Publication Type:: Journal Article
Citation:: Pattern Recognition, 2008, 41 (10), pp. 3179 - 3191
Issue Date:: 2008-01

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Full metadata record

Field	Value	Language
dc.contributor.author	Gao, X	en_US
dc.contributor.author	Xiao, B	en_US
dc.contributor.author	Tao, D https://orcid.org/0000-0001-7225-5449	en_US
dc.contributor.author	Li, X	en_US
dc.date.issued	2008-01	en_US
dc.identifier.citation	Pattern Recognition, 2008, 41 (10), pp. 3179 - 3191	en_US
dc.identifier.issn	0031-3203	en_US
dc.identifier.uri	http://hdl.handle.net/10453/17301
dc.description.abstract	This paper presents a novel algorithm for computing graph edit distance (GED) in image categorization. This algorithm is purely structural, i.e., it needs only connectivity structure of the graph and does not draw on node or edge attributes. There are tw	en_US
dc.publisher	Pergamon-elsevier Science Ltd	en_US
dc.relation.ispartof	Pattern Recognition	en_US
dc.relation.isbasedon	10.1016/j.patcog.2008.03.025	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Image Categorization: Graph Edit Distance Plus Edge Direction Histogram	en_US
dc.type	Journal Article
utslib.citation.volume	10	en_US
utslib.citation.volume	41	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0899 Other Information and Computing Sciences	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.issue	10	en_US
pubs.volume	41	en_US

Abstract:

This paper presents a novel algorithm for computing graph edit distance (GED) in image categorization. This algorithm is purely structural, i.e., it needs only connectivity structure of the graph and does not draw on node or edge attributes. There are tw

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http://hdl.handle.net/10453/17301