To stabilize and control a flying vehicle, attitude sensors are needed. Relative attitude sensors such as gyroscope tend to accumulate errors if not corrected periodically using absolute attitude sensors. Horizon sensor is one of the absolute sensors that is commonly used in satellites and recently in autonomous UAVs. This paper describes our early development of a horizon detection system, assuming the horizon as a straight line. The input image is pre-processed by converting to grayscale and applying a Gaussian filter. Then the Canny method performs edge detection and the detected edges are given to the line fitting algorithm to find the best fit line equation. We use the least square method to do line fitting. From the line equation obtained, roll and pitch angles are calculated. We implement the system using OpenCV and Python. We have conducted lab-scale experiments using images and video files. We make parameter adjustments to obtain good results. For the images we used, the recommended parameter values are Canny threshold (200, 250) and kernel size 3x3, and Gaussian filter size 3x3 to 5x5 in the Pre-processing stage. For other images, the values may need to be adjusted accordingly.


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    Title :

    Early development of horizon detection system based on OpenCV and Python


    Contributors:

    Conference:

    THE 8TH INTERNATIONAL SEMINAR ON AEROSPACE SCIENCE AND TECHNOLOGY – ISAST 2020 ; 2020 ; Bogor, Indonesia


    Published in:

    Publication date :

    2021-09-13


    Size :

    9 pages





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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