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Proceedings Paper

Enhancement of vision systems based on runway detection by image processing techniques
Author(s): N. Gulec; N. Sen Koktas
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Paper Abstract

An explicit way of facilitating approach and landing operations of fixed-wing aircraft in degraded visual environments is presenting a coherent image of the designated runway via vision systems and hence increasing the situational awareness of the flight crew. Combined vision systems, in general, aim to provide a clear view of the aircraft exterior to the pilots using information from databases and imaging sensors. This study presents a novel method that consists of image-processing and tracking algorithms, which utilize information from navigation systems and databases along with the images from daylight and infrared cameras, for the recognition and tracking of the designated runway through the approach and landing operation. Video data simulating the straight-in approach of an aircraft from an altitude of 5000 ft down to 100 ft is synthetically generated by a COTS tool. A diverse set of atmospheric conditions such as fog and low light levels are simulated in these videos. Detection and false alarm rates are used as the primary performance metrics. The results are presented in a format where the performance metrics are compared against the altitude of the aircraft. Depending on the visual environment and the source of the video, the performance metrics reach up to 98% for DR and down to 5% for FAR.

Paper Details

Date Published: 3 May 2012
PDF: 13 pages
Proc. SPIE 8360, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications IX, 83600T (3 May 2012); doi: 10.1117/12.923697
Show Author Affiliations
N. Gulec, SDT Space and Defence Technologies Inc. (Turkey)
N. Sen Koktas, SDT Space and Defence Technologies Inc. (Turkey)

Published in SPIE Proceedings Vol. 8360:
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications IX
Daniel J. Henry; Davis A. Lange; Dale Linne von Berg; Darrell L. Young; Kenneth L. Bernier; Jeff J. Guell; Sreekanth Danny Rajan, Editor(s)

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