Morphological approach for dashed lines detection

Gady Agam; Huizhu Luo; Its’hak Dinstein

doi:10.1007/3-540-61226-2_9

Morphological approach for dashed lines detection

Gady Agam, Huizhu Luo, Its’hak Dinstein

Department of Electrical & Computer Engineering

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

16 Scopus citations

Abstract

New directional morphological operators that have accurate selectivity and controllable strictness, are defined and applied to dashed fines detection and labeling. The proposed approach is based on adaptation of the directions and dimensions of newly defined tube-directional morphological operators to local characteristics of the data. The separation of maps and fine drawings, into four images containing respectively graphics, character strings, symbols, and dashes was presented in a previous paper. This paper presents an algorithm for detection and labeling of dashed lines, where the input is an image of dashes. Experimental results demonstrate very good detection even in cases where the dashed lines intersect.

Original language	English
Title of host publication	Graphics Recognition
Subtitle of host publication	Methods and Applications - 1st International Workshop, Selected Papers
Editors	Rangachar Kasturi, Karl Tombre
Publisher	Springer Verlag
Pages	92-105
Number of pages	14
ISBN (Print)	3540612262, 9783540612261
DOIs	https://doi.org/10.1007/3-540-61226-2_9
State	Published - 1 Jan 1996
Event	1st International Workshop on Graphics Recognition, 1995 - University Park, United States Duration: 10 Aug 1995 → 11 Aug 1995

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1072
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st International Workshop on Graphics Recognition, 1995
Country/Territory	United States
City	University Park
Period	10/08/95 → 11/08/95

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/3-540-61226-2_9

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Agam, G., Luo, H., & Dinstein, I. (1996). Morphological approach for dashed lines detection. In R. Kasturi, & K. Tombre (Eds.), Graphics Recognition: Methods and Applications - 1st International Workshop, Selected Papers (pp. 92-105). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1072). Springer Verlag. https://doi.org/10.1007/3-540-61226-2_9

Agam, Gady ; Luo, Huizhu ; Dinstein, Its’hak. / Morphological approach for dashed lines detection. Graphics Recognition: Methods and Applications - 1st International Workshop, Selected Papers. editor / Rangachar Kasturi ; Karl Tombre. Springer Verlag, 1996. pp. 92-105 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "New directional morphological operators that have accurate selectivity and controllable strictness, are defined and applied to dashed fines detection and labeling. The proposed approach is based on adaptation of the directions and dimensions of newly defined tube-directional morphological operators to local characteristics of the data. The separation of maps and fine drawings, into four images containing respectively graphics, character strings, symbols, and dashes was presented in a previous paper. This paper presents an algorithm for detection and labeling of dashed lines, where the input is an image of dashes. Experimental results demonstrate very good detection even in cases where the dashed lines intersect.",

author = "Gady Agam and Huizhu Luo and Its{\textquoteright}hak Dinstein",

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Agam, G, Luo, H & Dinstein, I 1996, Morphological approach for dashed lines detection. in R Kasturi & K Tombre (eds), Graphics Recognition: Methods and Applications - 1st International Workshop, Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1072, Springer Verlag, pp. 92-105, 1st International Workshop on Graphics Recognition, 1995, University Park, United States, 10/08/95. https://doi.org/10.1007/3-540-61226-2_9

Morphological approach for dashed lines detection. / Agam, Gady; Luo, Huizhu; Dinstein, Its’hak.
Graphics Recognition: Methods and Applications - 1st International Workshop, Selected Papers. ed. / Rangachar Kasturi; Karl Tombre. Springer Verlag, 1996. p. 92-105 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1072).

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

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N2 - New directional morphological operators that have accurate selectivity and controllable strictness, are defined and applied to dashed fines detection and labeling. The proposed approach is based on adaptation of the directions and dimensions of newly defined tube-directional morphological operators to local characteristics of the data. The separation of maps and fine drawings, into four images containing respectively graphics, character strings, symbols, and dashes was presented in a previous paper. This paper presents an algorithm for detection and labeling of dashed lines, where the input is an image of dashes. Experimental results demonstrate very good detection even in cases where the dashed lines intersect.

AB - New directional morphological operators that have accurate selectivity and controllable strictness, are defined and applied to dashed fines detection and labeling. The proposed approach is based on adaptation of the directions and dimensions of newly defined tube-directional morphological operators to local characteristics of the data. The separation of maps and fine drawings, into four images containing respectively graphics, character strings, symbols, and dashes was presented in a previous paper. This paper presents an algorithm for detection and labeling of dashed lines, where the input is an image of dashes. Experimental results demonstrate very good detection even in cases where the dashed lines intersect.

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Agam G, Luo H, Dinstein I. Morphological approach for dashed lines detection. In Kasturi R, Tombre K, editors, Graphics Recognition: Methods and Applications - 1st International Workshop, Selected Papers. Springer Verlag. 1996. p. 92-105. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-61226-2_9

Morphological approach for dashed lines detection

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