Airport Monitoring System: Robust Airplane Extraction against Variable Environmental Conditions

Takahiro AOKI; Osafumi NAKAYAMA; Morito SHIOHARA; Shigeru SASAKI; Yoshishige MURAKAMI

Airport Monitoring System: Robust Airplane Extraction against Variable Environmental Conditions

Takahiro AOKI, Osafumi NAKAYAMA, Morito SHIOHARA, Shigeru SASAKI, Yoshishige MURAKAMI

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We have developed an airport monitoring system that traces the movement of airplanes in the parking areas of airports. For this system, we have developed an image processing method, a two-stage normalized background subtraction method that can detect moving objects and determine the sizes of those objects under illumination changes, which are inevitable for outdoor monitoring systems. The two-stage method consists of local and global normalized subtraction. With this method, airplanes can be detected in a stable manner under illumination changes, which means that the brightness in each pixel is not constant due to changes in atmospheric phenomena, such as the shadows of clouds. And false detection problems due to the presence of boarding bridges are solved by utilizing differences in motion between an airplane and the boarding bridge, such as the direction of movement. We have evaluated this method using 140 hours of video images that contain scenes with a variety of conditions, such as the presence of cloud shadows, the turning on and off of lights, night, rainfall and so on. As a result, we have confirmed a 95% level of accuracy of airplane detection. This system is now in operation at Kansai International Airport and is performing most satisfactorily.

Publication: IEICE TRANSACTIONS on Information Vol.E84-D No.12 pp.1660-1667

Publication Date: 2001/12/01

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Type of Manuscript: Special Section PAPER (Special Issue on Machine Vision Applications)

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Takahiro AOKI, Osafumi NAKAYAMA, Morito SHIOHARA, Shigeru SASAKI, Yoshishige MURAKAMI, "Airport Monitoring System: Robust Airplane Extraction against Variable Environmental Conditions" in IEICE TRANSACTIONS on Information, vol. E84-D, no. 12, pp. 1660-1667, December 2001, doi: .
Abstract: We have developed an airport monitoring system that traces the movement of airplanes in the parking areas of airports. For this system, we have developed an image processing method, a two-stage normalized background subtraction method that can detect moving objects and determine the sizes of those objects under illumination changes, which are inevitable for outdoor monitoring systems. The two-stage method consists of local and global normalized subtraction. With this method, airplanes can be detected in a stable manner under illumination changes, which means that the brightness in each pixel is not constant due to changes in atmospheric phenomena, such as the shadows of clouds. And false detection problems due to the presence of boarding bridges are solved by utilizing differences in motion between an airplane and the boarding bridge, such as the direction of movement. We have evaluated this method using 140 hours of video images that contain scenes with a variety of conditions, such as the presence of cloud shadows, the turning on and off of lights, night, rainfall and so on. As a result, we have confirmed a 95% level of accuracy of airplane detection. This system is now in operation at Kansai International Airport and is performing most satisfactorily.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_12_1660/_p

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@ARTICLE{e84-d_12_1660,
author={Takahiro AOKI, Osafumi NAKAYAMA, Morito SHIOHARA, Shigeru SASAKI, Yoshishige MURAKAMI, },
journal={IEICE TRANSACTIONS on Information},
title={Airport Monitoring System: Robust Airplane Extraction against Variable Environmental Conditions},
year={2001},
volume={E84-D},
number={12},
pages={1660-1667},
abstract={We have developed an airport monitoring system that traces the movement of airplanes in the parking areas of airports. For this system, we have developed an image processing method, a two-stage normalized background subtraction method that can detect moving objects and determine the sizes of those objects under illumination changes, which are inevitable for outdoor monitoring systems. The two-stage method consists of local and global normalized subtraction. With this method, airplanes can be detected in a stable manner under illumination changes, which means that the brightness in each pixel is not constant due to changes in atmospheric phenomena, such as the shadows of clouds. And false detection problems due to the presence of boarding bridges are solved by utilizing differences in motion between an airplane and the boarding bridge, such as the direction of movement. We have evaluated this method using 140 hours of video images that contain scenes with a variety of conditions, such as the presence of cloud shadows, the turning on and off of lights, night, rainfall and so on. As a result, we have confirmed a 95% level of accuracy of airplane detection. This system is now in operation at Kansai International Airport and is performing most satisfactorily.},
keywords={},
doi={},
ISSN={},
month={December},}

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TY - JOUR
TI - Airport Monitoring System: Robust Airplane Extraction against Variable Environmental Conditions
T2 - IEICE TRANSACTIONS on Information
SP - 1660
EP - 1667
AU - Takahiro AOKI
AU - Osafumi NAKAYAMA
AU - Morito SHIOHARA
AU - Shigeru SASAKI
AU - Yoshishige MURAKAMI
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 12
JA - IEICE TRANSACTIONS on Information
Y1 - December 2001
AB - We have developed an airport monitoring system that traces the movement of airplanes in the parking areas of airports. For this system, we have developed an image processing method, a two-stage normalized background subtraction method that can detect moving objects and determine the sizes of those objects under illumination changes, which are inevitable for outdoor monitoring systems. The two-stage method consists of local and global normalized subtraction. With this method, airplanes can be detected in a stable manner under illumination changes, which means that the brightness in each pixel is not constant due to changes in atmospheric phenomena, such as the shadows of clouds. And false detection problems due to the presence of boarding bridges are solved by utilizing differences in motion between an airplane and the boarding bridge, such as the direction of movement. We have evaluated this method using 140 hours of video images that contain scenes with a variety of conditions, such as the presence of cloud shadows, the turning on and off of lights, night, rainfall and so on. As a result, we have confirmed a 95% level of accuracy of airplane detection. This system is now in operation at Kansai International Airport and is performing most satisfactorily.
ER -