一级车辆发动机号码识别系统

2020 International Conference on Advanced Robotics and Intelligent Systems (ARIS) Pub Date : 2020-08-01 DOI:10.1109/ARIS50834.2020.9205775

Cheng-Hsiung Yang, Han-Shen Feng

{"title":"一级车辆发动机号码识别系统","authors":"Cheng-Hsiung Yang, Han-Shen Feng","doi":"10.1109/ARIS50834.2020.9205775","DOIUrl":null,"url":null,"abstract":"This study proposes a one-stage vehicle engine number recognition system which avoids using the traditional three-stage recognition procedures of positioning, segmentation, and then character recognition, without the needs of image preprocessing procedures, we directly locate and recognizes the text targets in the vehicle engine image. The experiment using 926 labeled images via transfer learning to train our prediction model and then using this prediction model to test another 2310 unlabeled images, the overall accuracy achieved 99.48% and the execution time for recognize a single image is 234ms.","PeriodicalId":423389,"journal":{"name":"2020 International Conference on Advanced Robotics and Intelligent Systems (ARIS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"One-stage Vehicle Engine Number Recognition System\",\"authors\":\"Cheng-Hsiung Yang, Han-Shen Feng\",\"doi\":\"10.1109/ARIS50834.2020.9205775\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study proposes a one-stage vehicle engine number recognition system which avoids using the traditional three-stage recognition procedures of positioning, segmentation, and then character recognition, without the needs of image preprocessing procedures, we directly locate and recognizes the text targets in the vehicle engine image. The experiment using 926 labeled images via transfer learning to train our prediction model and then using this prediction model to test another 2310 unlabeled images, the overall accuracy achieved 99.48% and the execution time for recognize a single image is 234ms.\",\"PeriodicalId\":423389,\"journal\":{\"name\":\"2020 International Conference on Advanced Robotics and Intelligent Systems (ARIS)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Advanced Robotics and Intelligent Systems (ARIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ARIS50834.2020.9205775\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Advanced Robotics and Intelligent Systems (ARIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARIS50834.2020.9205775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

本研究提出了一种一期汽车发动机编号识别系统，避免了传统的定位、分割、字符识别三阶段识别流程，不需要图像预处理流程，直接对汽车发动机图像中的文本目标进行定位和识别。实验使用926张带标签的图像通过迁移学习训练我们的预测模型，然后使用该预测模型测试另外2310张未标记的图像，总体准确率达到99.48%，单个图像识别的执行时间为234ms。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

One-stage Vehicle Engine Number Recognition System

This study proposes a one-stage vehicle engine number recognition system which avoids using the traditional three-stage recognition procedures of positioning, segmentation, and then character recognition, without the needs of image preprocessing procedures, we directly locate and recognizes the text targets in the vehicle engine image. The experiment using 926 labeled images via transfer learning to train our prediction model and then using this prediction model to test another 2310 unlabeled images, the overall accuracy achieved 99.48% and the execution time for recognize a single image is 234ms.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2020 International Conference on Advanced Robotics and Intelligent Systems (ARIS)

自引率

0.00%

发文量