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Reading detection of needle-type instrument in a noisy environment using computer vision-based algorithms

Abstract : This study investigated the use of computer vision-based algorithms for detecting needle-type instrument readings in the cockpit of an aerial vehicle. A flight data recorder plays a crucial role in aviation safety investigations and flight operation review. In practice, not all aerial vehicles are equipped with flight data recorders, and this poses problems in the retrieval of instrument readings during investigations. Installing a lightweight recorder such as a camera in the cockpit to record the instrument panel is a solution to the mentioned problem. Although recorded flight data can be retrieved through human inspection, computer vision-based algorithms enable more rapid and efficient detection. Accordingly, this study developed two computer vision-based algorithms operated in both of the grayscale color space and the value layer of the hue-saturation-value color space. Performance of the four combinations is then compared and the best combination of algorithm along with operation space is suggested. The airspeed meter of a Bell 206 helicopter was selected to test the proposed detection algorithm in this study. GPS data and human inspection results were used as references. Herein, experimental results are presented, performance of algorithms is discussed, and conclusions are provided. This study contributes to aviation safety investigations and flight operation review involving aerial vehicles that are not equipped with flight data recorders.
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https://hal-enac.archives-ouvertes.fr/hal-03827314
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Soumis le : lundi 24 octobre 2022 - 15:36:27
Dernière modification le : lundi 24 octobre 2022 - 17:32:23

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Fu-Yuen Hsiao, Feng-Yu Chang, Pablo Vida, Brian Kuo, Pei-Chung Chen. Reading detection of needle-type instrument in a noisy environment using computer vision-based algorithms. Multimedia Tools and Applications, 2022, ⟨10.1007/s11042-022-13226-y⟩. ⟨hal-03827314⟩

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