Line detection method with robustness against contrast and width variation applied in gradient vector field

Yukiyasu Yoshinaga, Hidefumi Kobatake

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

This paper proposes a new method of extracting lines characterized as long and narrow bright regions, or curvilinear convex regions, in images. Generally, the contrast and the line width cause difficulty in extraction of ridgelines and skeletons. Therefore, this paper proposes the line convergence vector field model based on the intensity gradient vector field for a model of the curvilinear convex region. This model is independent of the contrast and the scale. Next, we propose the line convergence degree as a value of model evaluation for realizing the extraction of the curvilinear convex regions on the basis of this model. Then, we propose the Gradient-Angle-Weighted Hough Transform (GAWHT) for calculation of the evaluation value. Moreover, we obtain the theoretical value for the line convergence degree, as well as show its effectiveness in extraction of the curvilinear convex regions. We applied our method to artificial and practical images in experiment. The results show successfully extracted lines with a normalized index of the shape of the curvilinear convex region, demonstrating the effectiveness in extracting such regions free from the contrast and the scale.

Original languageEnglish
Pages (from-to)49-58
Number of pages10
JournalSystems and Computers in Japan
Volume31
Issue number3
DOIs
Publication statusPublished - Mar 1 2000

Fingerprint

Line Detection
Gradient vector
Vector Field
Robustness
Line
Hough transforms
Linewidth
Model Evaluation
Hough Transform
Method of Lines
Skeleton
Model
Model-based
Gradient
Angle
Evaluation
Experiments

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture
  • Computational Theory and Mathematics

Cite this

Line detection method with robustness against contrast and width variation applied in gradient vector field. / Yoshinaga, Yukiyasu; Kobatake, Hidefumi.

In: Systems and Computers in Japan, Vol. 31, No. 3, 01.03.2000, p. 49-58.

Research output: Contribution to journalArticle

@article{a7d1ce89c30e403885c8a86998e06cb0,
title = "Line detection method with robustness against contrast and width variation applied in gradient vector field",
abstract = "This paper proposes a new method of extracting lines characterized as long and narrow bright regions, or curvilinear convex regions, in images. Generally, the contrast and the line width cause difficulty in extraction of ridgelines and skeletons. Therefore, this paper proposes the line convergence vector field model based on the intensity gradient vector field for a model of the curvilinear convex region. This model is independent of the contrast and the scale. Next, we propose the line convergence degree as a value of model evaluation for realizing the extraction of the curvilinear convex regions on the basis of this model. Then, we propose the Gradient-Angle-Weighted Hough Transform (GAWHT) for calculation of the evaluation value. Moreover, we obtain the theoretical value for the line convergence degree, as well as show its effectiveness in extraction of the curvilinear convex regions. We applied our method to artificial and practical images in experiment. The results show successfully extracted lines with a normalized index of the shape of the curvilinear convex region, demonstrating the effectiveness in extracting such regions free from the contrast and the scale.",
author = "Yukiyasu Yoshinaga and Hidefumi Kobatake",
year = "2000",
month = "3",
day = "1",
doi = "10.1002/(SICI)1520-684X(200003)31:3<49::AID-SCJ6>3.0.CO;2-4",
language = "English",
volume = "31",
pages = "49--58",
journal = "Systems and Computers in Japan",
issn = "0882-1666",
publisher = "John Wiley and Sons Inc.",
number = "3",

}

TY - JOUR

T1 - Line detection method with robustness against contrast and width variation applied in gradient vector field

AU - Yoshinaga, Yukiyasu

AU - Kobatake, Hidefumi

PY - 2000/3/1

Y1 - 2000/3/1

N2 - This paper proposes a new method of extracting lines characterized as long and narrow bright regions, or curvilinear convex regions, in images. Generally, the contrast and the line width cause difficulty in extraction of ridgelines and skeletons. Therefore, this paper proposes the line convergence vector field model based on the intensity gradient vector field for a model of the curvilinear convex region. This model is independent of the contrast and the scale. Next, we propose the line convergence degree as a value of model evaluation for realizing the extraction of the curvilinear convex regions on the basis of this model. Then, we propose the Gradient-Angle-Weighted Hough Transform (GAWHT) for calculation of the evaluation value. Moreover, we obtain the theoretical value for the line convergence degree, as well as show its effectiveness in extraction of the curvilinear convex regions. We applied our method to artificial and practical images in experiment. The results show successfully extracted lines with a normalized index of the shape of the curvilinear convex region, demonstrating the effectiveness in extracting such regions free from the contrast and the scale.

AB - This paper proposes a new method of extracting lines characterized as long and narrow bright regions, or curvilinear convex regions, in images. Generally, the contrast and the line width cause difficulty in extraction of ridgelines and skeletons. Therefore, this paper proposes the line convergence vector field model based on the intensity gradient vector field for a model of the curvilinear convex region. This model is independent of the contrast and the scale. Next, we propose the line convergence degree as a value of model evaluation for realizing the extraction of the curvilinear convex regions on the basis of this model. Then, we propose the Gradient-Angle-Weighted Hough Transform (GAWHT) for calculation of the evaluation value. Moreover, we obtain the theoretical value for the line convergence degree, as well as show its effectiveness in extraction of the curvilinear convex regions. We applied our method to artificial and practical images in experiment. The results show successfully extracted lines with a normalized index of the shape of the curvilinear convex region, demonstrating the effectiveness in extracting such regions free from the contrast and the scale.

UR - http://www.scopus.com/inward/record.url?scp=0033875324&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033875324&partnerID=8YFLogxK

U2 - 10.1002/(SICI)1520-684X(200003)31:3<49::AID-SCJ6>3.0.CO;2-4

DO - 10.1002/(SICI)1520-684X(200003)31:3<49::AID-SCJ6>3.0.CO;2-4

M3 - Article

AN - SCOPUS:0033875324

VL - 31

SP - 49

EP - 58

JO - Systems and Computers in Japan

JF - Systems and Computers in Japan

SN - 0882-1666

IS - 3

ER -