RASTER TO VECTOR CONVERSION IN A MAP INTERPRETATION SYSTEM

Paul C.K. Kwok; T. John Turner

RASTER TO VECTOR CONVERSION IN A MAP INTERPRETATION SYSTEM

Paul C.K. Kwok
, T. John Turner

Research output: Contribution to conference › Paper › peer-review

1 Citation (Scopus)

Abstract

This paper describes the two components: thinning and vectorization, at the front end of a Geographic Information System. The raster dataset associated with a map is very large. A small D-sized drawing gives a 120 Mpixel document. The amount of page faults encountered by a typical conventional thinning algorithm is so large that the run time is dominated by disk I/O time. The Contour Generation Thinning Algorithm based on chain codes has been adopted and the amount of page faults are reduced by a factor equal to the total number of iterations. The skeleton is vectorized by traversing the chain codes and examining the raster. A tagging scheme is used that allows the vectorization process to identify all the end points and multiply-connected nodes.

Original language	English
Pages	165-168
Number of pages	4
Publication status	Published - 1990
Externally published	Yes
Event	2nd IAPR Workshop on Machine Vision Applications, MVA 1990 - Tokyo, Japan Duration: 28 Nov 1990 → 30 Nov 1990

Conference

Conference	2nd IAPR Workshop on Machine Vision Applications, MVA 1990
Country/Territory	Japan
City	Tokyo
Period	28/11/90 → 30/11/90

Cite this

@conference{122272d864cc41f0b080e8b7ce2e3570,

title = "RASTER TO VECTOR CONVERSION IN A MAP INTERPRETATION SYSTEM",

abstract = "This paper describes the two components: thinning and vectorization, at the front end of a Geographic Information System. The raster dataset associated with a map is very large. A small D-sized drawing gives a 120 Mpixel document. The amount of page faults encountered by a typical conventional thinning algorithm is so large that the run time is dominated by disk I/O time. The Contour Generation Thinning Algorithm based on chain codes has been adopted and the amount of page faults are reduced by a factor equal to the total number of iterations. The skeleton is vectorized by traversing the chain codes and examining the raster. A tagging scheme is used that allows the vectorization process to identify all the end points and multiply-connected nodes.",

author = "Kwok, \{Paul C.K.\} and Turner, \{T. John\}",

note = "Publisher Copyright: {\textcopyright} 1990 Proceedings of IAPR Workshop on Machine Vision Applications, MVA 1990. All rights reserved.; 2nd IAPR Workshop on Machine Vision Applications, MVA 1990 ; Conference date: 28-11-1990 Through 30-11-1990",

year = "1990",

language = "English",

pages = "165--168",

}

TY - CONF

T1 - RASTER TO VECTOR CONVERSION IN A MAP INTERPRETATION SYSTEM

AU - Kwok, Paul C.K.

AU - Turner, T. John

PY - 1990

Y1 - 1990

N2 - This paper describes the two components: thinning and vectorization, at the front end of a Geographic Information System. The raster dataset associated with a map is very large. A small D-sized drawing gives a 120 Mpixel document. The amount of page faults encountered by a typical conventional thinning algorithm is so large that the run time is dominated by disk I/O time. The Contour Generation Thinning Algorithm based on chain codes has been adopted and the amount of page faults are reduced by a factor equal to the total number of iterations. The skeleton is vectorized by traversing the chain codes and examining the raster. A tagging scheme is used that allows the vectorization process to identify all the end points and multiply-connected nodes.

AB - This paper describes the two components: thinning and vectorization, at the front end of a Geographic Information System. The raster dataset associated with a map is very large. A small D-sized drawing gives a 120 Mpixel document. The amount of page faults encountered by a typical conventional thinning algorithm is so large that the run time is dominated by disk I/O time. The Contour Generation Thinning Algorithm based on chain codes has been adopted and the amount of page faults are reduced by a factor equal to the total number of iterations. The skeleton is vectorized by traversing the chain codes and examining the raster. A tagging scheme is used that allows the vectorization process to identify all the end points and multiply-connected nodes.

UR - https://www.scopus.com/pages/publications/105016903847

M3 - Paper

AN - SCOPUS:105016903847

SP - 165

EP - 168

T2 - 2nd IAPR Workshop on Machine Vision Applications, MVA 1990

Y2 - 28 November 1990 through 30 November 1990

ER -

RASTER TO VECTOR CONVERSION IN A MAP INTERPRETATION SYSTEM

Abstract

Conference

Other files and links

Fingerprint

Cite this