• DocumentCode
    2407899
  • Title

    Recognition of the numbers of numerical civilian instrumentations based on bp neural network

  • Author

    Bai, Qiushi ; Zhang, Yunzhou ; Tan, Jiyuan ; Zhao, Limeng ; Qi, Zixin

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
  • fYear
    2009
  • fDate
    15-16 May 2009
  • Firstpage
    105
  • Lastpage
    108
  • Abstract
    With the rapid development of intelligent building, the requirement of automatic number identification of civilian instrumentations is increasingly urgent. This article uses iterative global threshold to binarize the images and then adopts projection method to locate the target regions and divide the numbers. The back-propagation neural network is used to recognize the numbers. The result indicates that the recognition rate is above 98%.
  • Keywords
    backpropagation; computerised instrumentation; image recognition; image segmentation; neural nets; automatic number identification; back-propagation neural network; intelligent building; iterative global threshold; numerical civilian instrumentations; projection method; Character recognition; Gray-scale; Histograms; Image recognition; Instruments; Intelligent structures; Iterative methods; Neural networks; Pattern recognition; Pixel; BP; civilian instrumentation; neural network; number recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Mechatronics and Automation, 2009. ICIMA 2009. International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-3817-4
  • Type

    conf

  • DOI
    10.1109/ICIMA.2009.5156571
  • Filename
    5156571