In-flight horizon line detection for airplanes using image processing

Lorand Lukacs
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Abstract

The paper presents an image processing based horizon recognition method used for aircraft attitude determination. The results are presented using data in the form of captured images by a wide angle lens video camera mounted on the vertical stabilizer of a two-seater sailplane during flight. The pixel coordinates of the visible horizon line are firstly obtained using robust image recognition techniques, successfully managing problems posed by the varying exposure levels in captured images. Adaptive contrast detecting methods are employed, solving challenges caused by different ground patterns and varying color intensity of the cloud base. A means for optimal projection of the detected horizon line on the image plane is also implemented. Distortion correction caused by the wide angle lens is employed, using the a-priori identified internal camera parameters. A method for alignment of aircraft and camera coordinate frames is also proposed, based on image processing. The pitch and yaw angles of the aircraft are calculated based on a concept tested and validated both in the laboratory and in the field. The presented method can be used for unmanned aerial vehicle (UAV) control when supplemented with additional sensors.
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基于图像处理的飞机飞行中地平线检测
提出了一种基于图像处理的飞机姿态识别方法。研究结果是利用安装在双座滑翔机垂直尾翼上的广角镜头摄像机在飞行过程中捕获的图像数据来呈现的。首先使用鲁棒图像识别技术获得可见地平线的像素坐标,成功地处理了捕获图像中不同曝光水平所带来的问题。采用自适应对比度检测方法,解决了不同地面图案和云基颜色强度变化带来的挑战。还实现了一种将检测到的水平线在图像平面上进行最佳投影的方法。利用先验识别的相机内部参数,对广角镜头引起的畸变进行校正。提出了一种基于图像处理的飞机和相机坐标帧对齐方法。飞机的俯仰角和偏航角是根据在实验室和现场测试和验证的概念计算的。在附加传感器的情况下,该方法可用于无人机的控制。
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