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Multiple Luminaire Identification in Airborne Images of Airport's Approach Lighting Using Mathematical Morphology With Variable Length Structuring Element

机译:具有可变长度结构元素的数学形态学在机场进近照明的机载图像中的多光源识别

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In night aviation, to land an aircraft, a pilot needs to be able to identify an airport. The approach lighting system (ALS) at an airport is used to provide identification and guidance to pilots. ALS consists of more than 100 luminaires which are installed in a defined pattern following strict guidelines by the International Civil Aviation Organization (ICAO). ICAO also has strict regulations for maintaining the performance level of the luminaires. However, to date there is no automated technique by which to monitor the performance of the lighting. We suggest using images of the lighting pattern captured using a camera placed inside an aircraft. Based on the information contained within these images, the performance of the luminaires has to be evaluated which requires identification of over 100 luminaires within the pattern of ALS image. This research proposes analysis of the pattern using morphology filters which use a variable length structuring element (VLSE). The dimension of the VLSE changes continuously within an image and varies for different images. A novel technique for automatic determination of the VLSE is proposed and it allows successful identification of the luminaires from the image data as verified through the use of simulated and real data.
机译:在夜间航空中,要使飞机降落,飞行员需要能够识别机场。机场的进场照明系统(ALS)用于为飞行员提供识别和指导。 ALS由100多个灯具组成,这些灯具按照国际民用航空组织(ICAO)的严格指南以定义的模式安装。国际民航组织也有严格的规定来维持灯具的性能水平。然而,迄今为止,还没有自动化的技术来监视照明的性能。我们建议使用放置在飞机内部的摄像头拍摄的照明图案的图像。基于这些图像中包含的信息,必须评估照明设备的性能,这需要在ALS图像的模式内识别100多个照明设备。这项研究提出了使用形态滤波器的模式分析,该滤波器使用可变长度结构元素(VLSE)。 VLSE的尺寸在图像中连续变化,并针对不同的图像而变化。提出了一种自动确定VLSE的新颖技术,该技术可以通过使用模拟和真实数据验证从图像数据中成功识别灯具。

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