Abstract
Aiming at the inefficiency of the manual sorting method used in sorting centers at district and county levels, an algorithm is proposed for the detection and recognition of three-segment waybill codes based on rotating frames and YOLOv5. First of all, the detection of rotation angle is achieved by converting the regression problem into a classification problem through a Circular smooth label to solve the influence of angle periodicity on training. Secondly, the improved algorithm is used to detect the waybill Logo, according to the position relationship between the Logo and the three-segment code, and then combine the Logo position and rotation angle to locate the three-segment code, and use Radon transform to correct the tilt of the three-segment code to improve the three-segment code locating accuracy. Finally, the template matching algorithm is used to identify the three-segment codes. The experimental results show that the proposed algorithm achieves 93.6% detection accuracy of courier Logo and more than 99% positioning accuracy of three-segment code, which can effectively improve courier sorting efficiency.
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Shen, J., Song, W. (2023). Three-Segment Waybill Code Detection and Recognition Algorithm Based on Rotating Frame and YOLOv5. In: **ong, N., Li, M., Li, K., **ao, Z., Liao, L., Wang, L. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 153. Springer, Cham. https://doi.org/10.1007/978-3-031-20738-9_24
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DOI: https://doi.org/10.1007/978-3-031-20738-9_24
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