Clustering of collinear line segments

Ann Scher; Michael Shneier; Azriel Rosenfeld

doi:10.1016/0031-3203(82)90003-6

Clustering of collinear line segments

Ann Scher
, Michael Shneier
, Azriel Rosenfeld^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

A number of methods are presented for finding clusters in collinear collections of line segments. The methods are of two kinds - merging methods and splitting methods. Both make use of an evaluation function, and several alternative functions are illustrated. The methods are evaluated using randomly generated clusters on backgrounds containing varying amounts of noise.

Original language	English
Pages (from-to)	85-91
Number of pages	7
Journal	Pattern Recognition
Volume	15
Issue number	2
DOIs	https://doi.org/10.1016/0031-3203(82)90003-6
State	Published - 1982
Externally published	Yes

Keywords

Clustering
Collinearity
Image processing
Line segments
Segmentation

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10.1016/0031-3203(82)90003-6

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@article{b4e6fcbace554dcca2dce26bd6b6883b,

title = "Clustering of collinear line segments",

abstract = "A number of methods are presented for finding clusters in collinear collections of line segments. The methods are of two kinds - merging methods and splitting methods. Both make use of an evaluation function, and several alternative functions are illustrated. The methods are evaluated using randomly generated clusters on backgrounds containing varying amounts of noise.",

keywords = "Clustering, Collinearity, Image processing, Line segments, Segmentation",

author = "Ann Scher and Michael Shneier and Azriel Rosenfeld",

note = "Funding Information: The merging methods initially assume that every individual line segment forms a trivial {"}cluster{"}. Each cluster attempts to expand by including neighboring segments, until an evaluation function prevents further additions. The methods may be sequential, for exam- The support of the U.S. Army Night Vision Laboratory and the Defense Advanced Research Projects Agency under Contract DAAG-53-76C-0138 (DARPA Order 3206) is gratefully acknowledged. *All correspondence to Dr. Rosenfeld at address above.",

year = "1982",

doi = "10.1016/0031-3203(82)90003-6",

language = "English",

volume = "15",

pages = "85--91",

journal = "Pattern Recognition",

issn = "0031-3203",

publisher = "Elsevier Ltd",

number = "2",

}

TY - JOUR

T1 - Clustering of collinear line segments

AU - Scher, Ann

AU - Shneier, Michael

AU - Rosenfeld, Azriel

N1 - Funding Information: The merging methods initially assume that every individual line segment forms a trivial "cluster". Each cluster attempts to expand by including neighboring segments, until an evaluation function prevents further additions. The methods may be sequential, for exam- The support of the U.S. Army Night Vision Laboratory and the Defense Advanced Research Projects Agency under Contract DAAG-53-76C-0138 (DARPA Order 3206) is gratefully acknowledged. *All correspondence to Dr. Rosenfeld at address above.

PY - 1982

Y1 - 1982

N2 - A number of methods are presented for finding clusters in collinear collections of line segments. The methods are of two kinds - merging methods and splitting methods. Both make use of an evaluation function, and several alternative functions are illustrated. The methods are evaluated using randomly generated clusters on backgrounds containing varying amounts of noise.

AB - A number of methods are presented for finding clusters in collinear collections of line segments. The methods are of two kinds - merging methods and splitting methods. Both make use of an evaluation function, and several alternative functions are illustrated. The methods are evaluated using randomly generated clusters on backgrounds containing varying amounts of noise.

KW - Clustering

KW - Collinearity

KW - Image processing

KW - Line segments

KW - Segmentation

UR - https://www.scopus.com/pages/publications/0019999335

U2 - 10.1016/0031-3203(82)90003-6

DO - 10.1016/0031-3203(82)90003-6

M3 - Article

AN - SCOPUS:0019999335

SN - 0031-3203

VL - 15

SP - 85

EP - 91

JO - Pattern Recognition

JF - Pattern Recognition

IS - 2

ER -

Clustering of collinear line segments

Abstract

Keywords

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