Vehicle identification number recognition based on neural network

Q3 Engineering 光电工程 Pub Date : 2021-01-15 DOI:10.12086/OEE.2021.200094
Meng Fanjun, Yin Dong
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引用次数: 0

Abstract

It is far essential to properly recognize the vehicle identification number (VIN) engraved on the car frame for vehicle surveillance and identification. In this paper, we propose an algorithm for recognizing rotational VIN im-ages based on neural network which incorporates two components: VIN detection and VIN recognition. Firstly, with lightweight neural network and text segmentation based on EAST, we attain efficient and excellent VIN detection performance. Secondly, the VIN recognition is regarded as a sequence classification problem. By means of connecting sequential classifiers, we predict VIN characters directly and precisely. For validating our algorithm, we collect a VIN dataset, which contains raw rotational VIN images and horizontal VIN images. Experimental results show that the algorithm we proposed achieves good performance on VIN detection and VIN recognition in real time.
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基于神经网络的车辆识别号码识别
正确识别镌刻在车架上的车辆识别号码对于车辆监控和识别至关重要。本文提出了一种基于神经网络的旋转VIN图像识别算法,该算法包含两个部分:VIN检测和VIN识别。首先,利用轻量级神经网络和基于EAST的文本分割,实现了高效、优异的识别码检测性能;其次,将VIN识别视为一个序列分类问题。通过连接顺序分类器,可以直接准确地预测VIN字符。为了验证我们的算法,我们收集了一个VIN数据集,其中包含原始的旋转VIN图像和水平VIN图像。实验结果表明,该算法在VIN检测和实时识别方面取得了较好的效果。
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来源期刊
光电工程
光电工程 Engineering-Electrical and Electronic Engineering
CiteScore
2.00
自引率
0.00%
发文量
6622
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