Train identification algorithm for EMU trouble detection
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摘要: 列车车号是其身份的唯一标识，动车组运行故障动态图像检测系统（TEDS）根据列车车号在图像库中找寻该列车拍摄的历史图像，以其比对现场采集图像，从而实现对运行列车状态的实时监测。然而动车组目前尚未安装射频识别电子标签，鉴于此，利用视频分析技术对动车组车号图像进行自动识别成为亟需解决的问题。文章提出一种基于语义共生概率的模板匹配算法对车号字符进行识别。实验结果表明，本算法对车号的识别正确率和有效性满足铁路总公司的相关要求，保障了TEDS的工作效果。
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关键词:
- 动车组运行故障动态图像检测系统 /
- 车牌定位分割 /
- 模板匹配 /
- 车号识别
Abstract: The train number is a unique identification of the train. The Trouble of moving EMU Detection System (TEDS) is aimed to detect the trouble of moving EMU images based on the matching between present image and previous one which searches in the image database of the train number. However the RFID electronic tag does not installed in the EMU. Hence, the EMU train number recognition has become urgent to solve the problem. The article proposed a template matching algorithm based on semantic symbiosis probability to identify the train number. The experimental results showed that the correct rate and effectiveness of the proposed approach could conform with the regulation of China Railways, ensure the effect of TEDS. -
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