复杂维修场景下飞机机号的定位识别方法

针对在复杂维修场景下飞机数量较多且体积庞大，无法实现准确高效的识别跟踪目标飞机的问题，提出基于YOLOv4目标检测的飞机机号识别算法，该方法首先利用YOLOv4检测算法获得飞机机型和预测框图像信息，然后通过图像处理算法实现飞机骨架细化，并依据机型获取飞机机号位置信息，最后利用OCR(optical character recognition)识别出目标飞机机号信息。实验结果证明，该算法实现了对飞机机号的识别，准确率为75%,帧率为30帧，可达到实时性的目的。

Positioning and identification method of aircraft number in complex maintenance scenarios

Aiming at the problem that target aircraft cannot be accurately and efficiently identified and followed in complex maintenance scenarios due to the large number and volume of aircraft, an aircraft number recognition algorithm is proposed in this paper based on YOLOv4 target detection. Firstly, the YOLOv4 detection algorithm was used by the method to obtain aircraft type and prediction block image information and then aircraft skeleton thinning was realized through image information. The location information of the aircraft number was obtained according to the aircraft type, and the OCR algorithm was used to identify the target aircraft number information. The experimental results show that the algorithm can recognize the aircraft number with an accuracy of 75% and a frame rate of 30 frames, which can achieve the purpose of real-time.