Fully convolutional network based ship plate recognition

Zhang, Weishan; Sun, Haoyun; Zhou, Jiehan; Liu, Xin; Zhang, Zhanmin; Min, Guizhi (2019-01-07)
 
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https://doi.org/10.1109/SMC.2018.00312

Zhang, Weishan
Sun, Haoyun
Zhou, Jiehan
Liu, Xin
Zhang, Zhanmin
Min, Guizhi
Institute of Electrical and Electronics Engineers
07.01.2019

W. Zhang, H. Sun, J. Zhou, X. Liu, Z. Zhang and G. Min, "Fully Convolutional Network Based Ship Plate Recognition," 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan, 2018, pp. 1803-1808, https://doi.org/10.1109/SMC.2018.00312

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doi:https://doi.org/10.1109/SMC.2018.00312
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https://urn.fi/URN:NBN:fi-fe2020042822734
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Abstract

Ship plate recognition is challenging due to variations of plate locations and text types. This paper proposes an effcient Fully Convolutional Network based Plate Recognition approach FCNPR, which uses a CNN (Convolutional Neural Network) to locate ships, then detects plate text lines with the fully convolutional network (FCN). The recognition accuracy is improved with integrating the AIS (Automatic Identification System) information. The actual FCNPR deployment demonstrates that it can work reliably with a high accuracy for satisfying practical usages.

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