A rail detection algorithm based on pair particles filtering

Ji Sang Bae, Jong-Ok Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Safety of mass transportation like train cannot be emphasized enough, and accurate rail detection in the direction of progress can be useful to the safe operation of a train. In this paper, we propose a new pair particles filtering based rail detection algorithm that simultaneously predicts a pair position of left and right rails. Multiple pairs of particles are first generated from the previously detected rails, and features of a pair particles position, rail gauge, and gradient magnitude are used to detect the positions of pair rails. The proposed pair particles filtering based method flexibly detects both straight and curved rails robustly. Experiments with various actual rail images show plausible detection results of the proposed method.

Original languageEnglish
Title of host publicationProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1440-1443
Number of pages4
ISBN (Electronic)9781538615423
DOIs
Publication statusPublished - 2018 Feb 5
Event9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 - Kuala Lumpur, Malaysia
Duration: 2017 Dec 122017 Dec 15

Publication series

NameProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Volume2018-February

Other

Other9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Country/TerritoryMalaysia
CityKuala Lumpur
Period17/12/1217/12/15

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Information Systems
  • Signal Processing

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