Similarity invariant delaunay graph matching

Dongjoe Shin, Tardi Tjahjadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Delaunay tessellation describes a set of arbitrarily distributed points as unique triangular graphs which preserves most local point configuration called a clique regardless of noise addition and partial occlusion. In this paper, this structure is utilised in a matching method and proposed a clique-based Hausdorff Distance (HD) to address point pattern matching problems. Since the proposed distance exploits similarity invariant features extracted from a clique, it is invariant to rotation, translation and scaling. Furthermore, it inherits noise robustness from HD and has partial matching ability because matching performs on local entities. Experimental results show that the proposed method performs better than the existing variants of the general HD.
Original languageEnglish
Title of host publicationStructural, Syntactic, and Statistical Pattern Recognition
Subtitle of host publicationJoint IAPR International Workshop, SSPR & SPR 2008, Orlando, USA, December 4-6, 2008. Proceedings
EditorsNiels da Vitoria Lobo, Takis Kasparis, Fabio Roli, James T. Kwok, Michael Georgiopoulos
ISBN (Electronic)978-3-540-89689-0
ISBN (Print)978-3-540-89688-3
Publication statusPublished - Dec 2008
Externally publishedYes
EventStructural, Syntactic and statistical pattern recognition - Orlando , United States
Duration: 4 Dec 20086 Dec 2008

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceStructural, Syntactic and statistical pattern recognition
Abbreviated titleSSPR SPR 2008
Country/TerritoryUnited States


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