Computer Vision System for Cabin Door Detection and Location

Bojan Andonovski, Jianliang Wang

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

4 Citations (Scopus)

Abstract

This paper describes the outcomes of a framework for aircraft door position identification with visual camera using common features that can be found in all commercial airplanes, which guides the aerobridge to automatically and reliably dock (Precision of 0.5cm), with minimal human intervention. The system has to work day and night, rain or shine under all-weather conditions. The proposed solution consists of a suite of relevant extracted and identified features that characterize aircraft door (e.g. door windows, handle, text, footplate, arrow, frame lines). Furthermore, the work focuses on a final door position confirmation accomplished by the logical structure for the decision process for the identification of the aircraft door using the various features. In that way we are able to build confidence level with appropriate structural (logical component connection) organization. Thus, the aircraft door frame can be accurately identified with a very small error (in the range of a couple of cm) and eliminate risk of injuring the personnel or damaging the airplane.

Original languageEnglish
Title of host publication2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1537-1542
Number of pages6
ISBN (Electronic)9781538695821
DOIs
Publication statusPublished - 18 Dec 2018
Externally publishedYes
Event15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018 - Singapore, Singapore
Duration: 18 Nov 201821 Nov 2018

Publication series

Name2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018

Conference

Conference15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
Country/TerritorySingapore
CitySingapore
Period18/11/1821/11/18

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Optimization

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