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Authors: J. H. Niblock ; K. McMenemy ; S. Ferguson and J. X. Peng

Affiliation: Queen’s University Belfast, United Kingdom

Keyword(s): Airport approach lighting, autonomous tracking, grey level assessment.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Feature Extraction ; Features Extraction ; Human-Computer Interaction ; Image and Video Analysis ; Image Formation and Preprocessing ; Image Formation, Acquisition Devices and Sensors ; Implementation of Image and Video Processing Systems ; Informatics in Control, Automation and Robotics ; Matching Correspondence and Flow ; Methodologies and Methods ; Motion and Tracking ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Physiological Computing Systems ; Signal Processing, Sensors, Systems Modeling and Control

Abstract: The central aim of this research is to develop an an autonomous measurement system for assessing the performance of an airport lighting pattern. The system improves safety with regard to aircraft landing procedures by ensuring the airport lighting is properly maintained and conforms to current standards and recommendations laid down by the International Civil Aviation Organisation (ICAO). A vision system, mounted in the cockpit of an aircraft, is capable of capturing sequences of airport lighting images during a normal approach to an aerodrome. These images are post-processeda to determine the grey level of the approach lighting pattern (ALP). In this paper, two tracking algorithms are presented which can detect and track individual luminaires throughout the complete image sequence. The effective tracking of the luminaires is central to the long term goal of this research, which is to assess the performance of the luminaires’ from the recorded grey level data extracted for each detec ted luminaire. The two algorithms presented are the Niblock-McMenemy (NM) feature tracking algorithm has been optimised for the specific task of airport lighting and to assess its effectiveness it has been compared to the Kanade-Lucus-Tomasi (KLT) feature tracking algorithm. In order to validate both algorithms a synthetic 3D model of the ALP is presented. To further assess the robustness of the algorithms results from an actual approach to a UK aerodromeb are presented. The results show that although both KLT and NM feature trackers are both effective in tracking airport lighting the NM algorithm is better suited to the task due to its reliable grey level information. Limitations, such as the static window size, of the KLT algorithm result in a lossy grey level data and hence lead to inaccurate results. (More)

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Paper citation in several formats:
H. Niblock, J.; McMenemy, K.; Ferguson, S. and X. Peng, J. (2007). AUTONOMOUS TRACKING SYSTEM FOR AIRPORT LIGHTING QUALITY CONTROL. In Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP; ISBN 978-972-8865-74-0; ISSN 2184-4321, SciTePress, pages 317-324. DOI: 10.5220/0002039903170324

@conference{visapp07,
author={J. {H. Niblock}. and K. McMenemy. and S. Ferguson. and J. {X. Peng}.},
title={AUTONOMOUS TRACKING SYSTEM FOR AIRPORT LIGHTING QUALITY CONTROL},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP},
year={2007},
pages={317-324},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002039903170324},
isbn={978-972-8865-74-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications (VISIGRAPP 2007) - Volume 2: VISAPP
TI - AUTONOMOUS TRACKING SYSTEM FOR AIRPORT LIGHTING QUALITY CONTROL
SN - 978-972-8865-74-0
IS - 2184-4321
AU - H. Niblock, J.
AU - McMenemy, K.
AU - Ferguson, S.
AU - X. Peng, J.
PY - 2007
SP - 317
EP - 324
DO - 10.5220/0002039903170324
PB - SciTePress