• Optical Communication Technology
  • Vol. 45, Issue 2, 6 (2021)
LIU Mengqiao and XU Ning
Author Affiliations
  • [in Chinese]
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    DOI: 10.13921/j.cnki.issn1002-5561.2021.02.002 Cite this Article
    LIU Mengqiao, XU Ning. Characters recognition algorithm of optical cable surface inkjet code based on OpenCV[J]. Optical Communication Technology, 2021, 45(2): 6 Copy Citation Text show less

    Abstract

    There are many disadvantages in manual identification of optical cable inkjet code characters, so the automatic identification technology of optical cable is urgently needed. Aiming at the characteristics of dot matrix characters in optical cable, an online optical cable character recognition system is proposed, the simulation research and parameter optimization of three character recognition algorithms such as template matching, artificial neural network and support vector machine are carried out, and the advantages and disadvantages of these three algorithms are compared. The influence of parameters of artificial neural network and support vector machine on recognition accuracy and training time is analyzed. The simulation results show that under the same test set, the artificial neural network algorithm has the highest recognition rate, the support vector machine algorithm has excellent performance when the number of training samples is small, and the template matching algorithm has the lowest complexity.