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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Opto-Electronic Engineering
ISSN: 1003-501X
CN: 51-1346/O4
Monthly, included in CA, Scopus, CSCD
CN: 51-1346/O4
Monthly, included in CA, Scopus, CSCD
Vehicle identification number recognition based on neural network
Author Affiliations
Correspondence: yindong@ustc.edu.cn
First published at:Jan 15, 2021
Abstract
References
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Key Research and Development Projects of Anhui Province (804a09020049)
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Meng Fanjun, Yin Dong. Vehicle identification number recognition based on neural network[J]. Opto-Electronic Engineering, 2021, 48(1): 200094.
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