Open AccessDetecting Corresponding Vertex Pairs between Planar Tessellation Datasets with Agglomerative Hierarchical Cell-Set Matching
Author(s) -
Yong Huh,
Kiyun Yu,
Woojin Park
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0157913
Subject(s) - hierarchical clustering , vertex (graph theory) , matching (statistics) , cluster analysis , tessellation (computer graphics) , set (abstract data type) , pattern recognition (psychology) , planar , computer science , combinatorics , mathematics , artificial intelligence , graph , geometry , statistics , computer graphics (images) , programming language
This paper proposes a method to detect corresponding vertex pairs between planar tessellation datasets. Applying an agglomerative hierarchical co-clustering, the method finds geometrically corresponding cell-set pairs from which corresponding vertex pairs are detected. Then, the map transformation is performed with the vertex pairs. Since these pairs are independently detected for each corresponding cell-set pairs, the method presents improved matching performance regardless of locally uneven positional discrepancies between dataset. The proposed method was applied to complicated synthetic cell datasets assumed as a cadastral map and a topographical map, and showed an improved result with the F-measures of 0.84 comparing to a previous matching method with the F-measure of 0.48.