Treffer: Matching planar maps
Title:
Matching planar maps
Authors:
Source:
Journal of algorithms (Print). 49(2):262-283
Publisher Information:
San Diego, CA: Elsevier, 2003.
Publication Year:
2003
Physical Description:
print, 5 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Combinatoire. Structures ordonnées, Combinatorics. Ordered structures, Combinatoire, Combinatorics, Théorie des graphes, Graph theory, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Programmation mathématique, Mathematical programming, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Informatique théorique, Computer theory, Informática teórica, Mesure Fréchet, Fréchet measure, Medida Fréchet, Mesure de distance, Distance measurement, Medición distancia, Programmation dynamique, Dynamic programming, Programación dinámica, Reconnaissance forme, Pattern recognition, Reconocimiento patrón, Segment droite, Line segment, Segmento recta, Système information, Information system, Sistema información, Vision ordinateur, Computer vision, Visión ordenador, Algorithme combinatoire, Combinatorial algorithm, Algorithme graphe, Graph algorithm, Application plane, Planar map, Courbe polygonal, Polygonal curve
Document Type:
Fachzeitschrift
Article
File Description:
text
Language:
English
Author Affiliations:
Freie Universität Berlin, Institut für Informatik, Takustrasse 9, 14195 Berlin, Germany
University of Arizona, Computer Science Department, 1040 E 4th Street, Tucson, AZ 85721-0077, United States
University of Arizona, Computer Science Department, 1040 E 4th Street, Tucson, AZ 85721-0077, United States
ISSN:
0196-6774
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Mathematics
Operational research. Management
Mathematics
Operational research. Management
Accession Number:
edscal.15272407
Database:
PASCAL Archive
Weitere Informationen
The subject of this paper are algorithms for measuring the similarity of patterns of line segments in the plane, a standard problem in, e.g., computer vision, geographic information systems, etc. More precisely, we define feasible distance measures that reflect how close a given pattern H is to some part of a larger pattern G. These distance measures are generalizations of the well-known Fréchet distance for curves. We first give an efficient algorithm for the case that H is a polygonal curve and G is a geometric graph. Then, slightly relaxing the definition of distance measure, we give an algorithm for the general case where both, H and G, are geometric graphs.