### Abstract

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 will 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 will 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 will give an algorithm for the general case where both, H and G, are geometric graphs.

Original language | English (US) |
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Title of host publication | Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms |

Editors | J Schewel |

Pages | 589-598 |

Number of pages | 10 |

State | Published - 2003 |

Event | Configuralble Computing: Technology and Applications - Boston, MA, United States Duration: Nov 2 1998 → Nov 3 1998 |

### Other

Other | Configuralble Computing: Technology and Applications |
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Country | United States |

City | Boston, MA |

Period | 11/2/98 → 11/3/98 |

### Fingerprint

### ASJC Scopus subject areas

- Chemical Health and Safety
- Software
- Safety, Risk, Reliability and Quality
- Discrete Mathematics and Combinatorics

### Cite this

*Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms*(pp. 589-598)

**Matching planar maps.** / Alt, Helmut; Efrat, Alon; Rote, Günter; Wenk, Carola.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms.*pp. 589-598, Configuralble Computing: Technology and Applications, Boston, MA, United States, 11/2/98.

}

TY - GEN

T1 - Matching planar maps

AU - Alt, Helmut

AU - Efrat, Alon

AU - Rote, Günter

AU - Wenk, Carola

PY - 2003

Y1 - 2003

N2 - 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 will 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 will 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 will give an algorithm for the general case where both, H and G, are geometric graphs.

AB - 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 will 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 will 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 will give an algorithm for the general case where both, H and G, are geometric graphs.

UR - http://www.scopus.com/inward/record.url?scp=0038416016&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0038416016&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0038416016

SP - 589

EP - 598

BT - Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms

A2 - Schewel, J

ER -