TY - GEN
T1 - Computer Vision System for Cabin Door Detection and Location
AU - Andonovski, Bojan
AU - Wang, Jianliang
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/18
Y1 - 2018/12/18
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85060789479&partnerID=8YFLogxK
U2 - 10.1109/ICARCV.2018.8581250
DO - 10.1109/ICARCV.2018.8581250
M3 - Conference contribution
AN - SCOPUS:85060789479
T3 - 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
SP - 1537
EP - 1542
BT - 2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
Y2 - 18 November 2018 through 21 November 2018
ER -