计算机应用与软件2024，Vol.41Issue(1)：177-182,6.DOI:10.3969/j.issn.1000-386x.2024.01.026
基于Faster-RCNN和先验知识的车架VIN码识别方法
FRAME VIN CODE RECOGNITION METHOD BASED ON FASTER-RCNN AND PRIOR KNOWLEDGE
赵珣 1张新峰 1边浩南1
作者信息
- 1. 北京工业大学信息学部 北京 100124
- 折叠
摘要
Abstract
In order to increase the working efficiency of vehicle inspection office and overcome the problem of low accuracy of long character string recognition,we proposed a VIN(Vehicle Identification Number)recognition model based on the existing deep convolutional neural network model,which combines Faster R-CNN as the backbone network with the prior knowledge of VIN image.According to the characteristic of VIN image,Faster R-CNN was selected for character level positioning and recognition.In order to solve the problem of missing characters in long character recognition,we used the coordinates of the characters before and after the missing position to locate the missing characters.We used the inception network to recognize the character regions obtained from the omission.By using prior knowledge flexibly,the accuracy of our method is 31.7 percentage points higher than the model of using Faster R-CNN only,the recognition rate reaches 64％,and that is also higher than the accuracy of prevailing OCR model in the recognition of character string that longer than 15.关键词
OCR/Faster RCNN/先验知识/长字符串Key words
OCR/Faster R-CNN/Prior knowledge/Long string分类
信息技术与安全科学引用本文复制引用
赵珣,张新峰,边浩南..基于Faster-RCNN和先验知识的车架VIN码识别方法[J].计算机应用与软件,2024,41(1):177-182,6.
