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朱俊霖, 段钰, 滕凯, 邢宗义, 宫伟. 基于图像处理的城轨列车车号识别系统[J]. 铁路计算机应用, 2022, 31(9): 20-24. DOI: 10.3969/j.issn.1005-8451.2022.09.04
引用本文: 朱俊霖, 段钰, 滕凯, 邢宗义, 宫伟. 基于图像处理的城轨列车车号识别系统[J]. 铁路计算机应用, 2022, 31(9): 20-24. DOI: 10.3969/j.issn.1005-8451.2022.09.04
ZHU Junlin, DUAN Yu, TENG Kai, XING Zongyi, GONG Wei. Urban rail train number recognition system based on image processing[J]. Railway Computer Application, 2022, 31(9): 20-24. DOI: 10.3969/j.issn.1005-8451.2022.09.04
Citation: ZHU Junlin, DUAN Yu, TENG Kai, XING Zongyi, GONG Wei. Urban rail train number recognition system based on image processing[J]. Railway Computer Application, 2022, 31(9): 20-24. DOI: 10.3969/j.issn.1005-8451.2022.09.04

基于图像处理的城轨列车车号识别系统

Urban rail train number recognition system based on image processing

  • 摘要: 针对现有射频识别标签易脱落损坏导致丢失车号的问题,提出了基于图像处理的城轨列车车号识别系统。利用工业相机拍摄城轨列车侧面车号,再采用加速稳健特征算法和变换不变低秩纹理方法对拍摄到的图片进行车号定位、校正、分割操作,利用Visual Geometry Group-16(VGG-16)网络模型对分割好的车号字符进行识别。试验结果表明,该系统具有鲁棒性好、识别准确率高等特点,能够满足城轨列车车号获取的要求。

     

    Abstract: Aiming at the problem that existing RFID tags were easy to fall off and damage, resulting in the loss of vehicle number, this paper proposed an urban rail train number recognition system based on image processing. The paper used industrial cameras to take pictures of train numbers on the side of urban rail trains, and then used Speed Up Robust Features(SURF) algorithm and Transform Invariant Low-rank Textures(TILT) method to locate, correct and segment the captured pictures, used the VGG-16 network model to recognize the segmented train number characters. The test results show that the system has good robustness and high recognition accuracy, and can meet the requirements of urban rail train number acquisition.

     

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