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To enhance the automation level of remote apron control towers, a simple and effective automatic aircraft tail number recognition algorithm is proposed. For aircraft images obtained by remote apron control towers, the tail number area is first quickly located through the Hough transform. Then, YOLOv12 is used to accurately locate the tail number character areas. After that, the tail number is segmented by the threshold method, and finally, the recognition is completed using the hole-based template matching method. Experimental results show that this algorithm has a good effect on aircraft tail number recognition and strong robustness, with broad application prospects.

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Automatic Tail Number Recognition for Civil Aviation Remote Apron Control Towers

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Aijun Cui,
  • Xuan He,
  • Kai Wang,
  • Mozhen Tang,
  • Donglin He

摘要

To enhance the automation level of remote apron control towers, a simple and effective automatic aircraft tail number recognition algorithm is proposed. For aircraft images obtained by remote apron control towers, the tail number area is first quickly located through the Hough transform. Then, YOLOv12 is used to accurately locate the tail number character areas. After that, the tail number is segmented by the threshold method, and finally, the recognition is completed using the hole-based template matching method. Experimental results show that this algorithm has a good effect on aircraft tail number recognition and strong robustness, with broad application prospects.