OBJECT DETECTION METHOD APPLICATION TO RUNWAY IMAGERY IN LOW VISIBILITY CONDITIONS

Abstract

When ensuring aviation safety, the outboard environment awareness of the crew in low visibility conditions is especially important. The information about the runway condition and availability of any obstacles is crucial. There are ground-based obstacle detection systems, but currently only large airports are equipped with them. There are Enhanced Vision Systems designed for application on aircraft in low visibility conditions. The main goal of this research is to develop the means of runway obstacle recognition in low visibility conditions, which are to improve the capabilities of Enhanced Vision Systems. The research covers only the methods for static image object detection. The analysis of the runway markings, objects and possible obstacles is performed. Targets for acquisition are defined. The simulation of runway images is performed on full-flight simulator in low visibility conditions. The requirements for features descriptors, recognition and detection methods are defined and methods for research are defined. The paper provides evaluation of method applicability to runway pictures taken in poor visibility conditions above and below the decision height taking into account various characteristics. The covered methods solve the problem of detecting objects of the runway in low visibility conditions for static image. Conclusions about the possibility to use the studied methods in Enhanced Vision Systems are made. Further development of optimization methods is required to perform detection in video sequences in real time. The results of this work are relevant to the tasks of avionics, computer vision and image processing.

Keywords

• система улучшенного видения
• распознавание объектов
• взлетно-посадочная полоса
• обнаружение объектов на изображениях
• анализ изображений