Line segment detection based on probability map

Fei Wu, Sun Li, Bo Wang, Jinlei Ma

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

In this paper, a novel line segment detection method based on probability map is proposed. Firstly, the local gradient information is used to estimate if a pixel belongs to a line segment and a probability map is produced. The probability map combines gradient orientation with gradient magnitude information and can provide candidate points for edge chain extraction. Secondly, these candidate points are connected together to generate edge chains and then edge chains are split to candidate line segments by using least square line fitting method. At last, we apply Helmholtz principle to validate the detected line segments. Experimental results demonstrate that the proposed method outperforms other methods in term of visual comparison and quantitative assessment.

Original languageEnglish
Title of host publicationProceedings of the 36th Chinese Control Conference, CCC 2017
EditorsTao Liu, Qianchuan Zhao
PublisherIEEE Computer Society
Pages10875-10879
Number of pages5
ISBN (Electronic)9789881563934
DOIs
Publication statusPublished - 7 Sept 2017
Event36th Chinese Control Conference, CCC 2017 - Dalian, China
Duration: 26 Jul 201728 Jul 2017

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference36th Chinese Control Conference, CCC 2017
Country/TerritoryChina
CityDalian
Period26/07/1728/07/17

Keywords

  • Helmholtz principle
  • Line segment detection
  • least square line fitting
  • probability map

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