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Barcode Recognizable System Implementing Based on AM5728

Received: 29 November 2016     Published: 1 December 2016
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Abstract

To refine the implementation of industrial camera requirements in terms of barcode identification, speeding the barcode image acquisition and processing challenges, as well as the defect of low accuracy. We proposed a barcode recognition framework based on AM5728 embedded system, which employed industrial CCD to scan the barcode image, moreover, integrated with AM5728 visual development platform to manipulate the collected images. After that, decoding information is yielded from series of algorithms refer to convolution filtering, barcode positioning as well as recognition facilitated by AM5728 visual development platform. Experimental outcomes validated that the accuracy of our system recognition rate can reach up to satisfied 100% in the threshold condition, with 20 frames per second barcode images recognition rate.

Published in Automation, Control and Intelligent Systems (Volume 4, Issue 6)
DOI 10.11648/j.acis.20160406.12
Page(s) 89-94
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Barcode, Embedded System, AM5728, Barcode Identification, System Design, Convolution Filtering

References
[1] Yang Jiayao, Research on embedded one dimensional barcode recognition system based on image processing, PhD diss. Changsha University of Science and Technology, China, 2012.
[2] Zu Xiong, Research and implementation of barcode identification technology based on iPhone platform, master's thesis, Nanjing University of Aeronautics and Astronautics, China, 2010.
[3] Jiang Liang, “Barcode positioning and recognition based on method of run length encoding idea,” information network security, 2012, 2: 16-19.
[4] Liu Wenjun, Research on the positioning and recognition method of commercial barcode based on image processing master's thesis, Dalian University of Technology, China, 2013.
[5] Chi Shuzhen, The development of barcode software based on plug-in mode and related technology research master's thesis, Jilin University, China, 2011.
[6] Wang Yajing, “EAN-13 barcode recognition algorithm based on image processing,” Journal of Shandong University of Technology (NATURAL SCIENCE EDITION), 2005, 19 (4): 14-18.
[7] Lv Wei, Bai Sha, Zhou Linyu. “Application of Siemens S7-1200 PLC in Bar Code Identification,” Industrial Control Computer, 2015, 6 (28): 144-145.
[8] Zhang Xiling, Shi Weibin, “Study of Indoor Localization Technique Based on WSN,” Electronic Science and Technology, 2015, 10 (28): 115-118.
[9] Shi Zhenlei, Based on image processing of one-dimensional bar code identification, master's thesis, Shandong university of science and technology, China, 2014.
[10] Liu Bing, Liu Xiaopeng, Zeng Xiangliang, “intelligent shopping cart design Based on barcode recognition technology,” forest engineering, 2012, 28 (6): 32-35.
[11] Chen Lan, Fixed bar code identification system research and implementation base on image, master's thesis, University of Chinese academy of sciences, China, 2015.
[12] Liu Licai, Du Chuanhong, Liang Lixiu C, “The realization of the barcode scanner under QT programming,” Science and technology innovation and application, 2014, 28: 25-32.
[13] Liu Song, Lu Yixiang, Sun Dong, “USB camera bar code identification,” Microelectronics & Computer, 2014, 1 (31): 47-51.
Cite This Article
  • APA Style

    Xicai Li, Junsheng Shi, Xiaoqiao Huang, Yonghang Tai, Chongde Zi, et al. (2016). Barcode Recognizable System Implementing Based on AM5728. Automation, Control and Intelligent Systems, 4(6), 89-94. https://doi.org/10.11648/j.acis.20160406.12

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    ACS Style

    Xicai Li; Junsheng Shi; Xiaoqiao Huang; Yonghang Tai; Chongde Zi, et al. Barcode Recognizable System Implementing Based on AM5728. Autom. Control Intell. Syst. 2016, 4(6), 89-94. doi: 10.11648/j.acis.20160406.12

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    AMA Style

    Xicai Li, Junsheng Shi, Xiaoqiao Huang, Yonghang Tai, Chongde Zi, et al. Barcode Recognizable System Implementing Based on AM5728. Autom Control Intell Syst. 2016;4(6):89-94. doi: 10.11648/j.acis.20160406.12

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  • @article{10.11648/j.acis.20160406.12,
      author = {Xicai Li and Junsheng Shi and Xiaoqiao Huang and Yonghang Tai and Chongde Zi and Huan Yang and Xingyu Yang and Zhiwei Deng and Feiyan Li},
      title = {Barcode Recognizable System Implementing Based on AM5728},
      journal = {Automation, Control and Intelligent Systems},
      volume = {4},
      number = {6},
      pages = {89-94},
      doi = {10.11648/j.acis.20160406.12},
      url = {https://doi.org/10.11648/j.acis.20160406.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20160406.12},
      abstract = {To refine the implementation of industrial camera requirements in terms of barcode identification, speeding the barcode image acquisition and processing challenges, as well as the defect of low accuracy. We proposed a barcode recognition framework based on AM5728 embedded system, which employed industrial CCD to scan the barcode image, moreover, integrated with AM5728 visual development platform to manipulate the collected images. After that, decoding information is yielded from series of algorithms refer to convolution filtering, barcode positioning as well as recognition facilitated by AM5728 visual development platform. Experimental outcomes validated that the accuracy of our system recognition rate can reach up to satisfied 100% in the threshold condition, with 20 frames per second barcode images recognition rate.},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - Barcode Recognizable System Implementing Based on AM5728
    AU  - Xicai Li
    AU  - Junsheng Shi
    AU  - Xiaoqiao Huang
    AU  - Yonghang Tai
    AU  - Chongde Zi
    AU  - Huan Yang
    AU  - Xingyu Yang
    AU  - Zhiwei Deng
    AU  - Feiyan Li
    Y1  - 2016/12/01
    PY  - 2016
    N1  - https://doi.org/10.11648/j.acis.20160406.12
    DO  - 10.11648/j.acis.20160406.12
    T2  - Automation, Control and Intelligent Systems
    JF  - Automation, Control and Intelligent Systems
    JO  - Automation, Control and Intelligent Systems
    SP  - 89
    EP  - 94
    PB  - Science Publishing Group
    SN  - 2328-5591
    UR  - https://doi.org/10.11648/j.acis.20160406.12
    AB  - To refine the implementation of industrial camera requirements in terms of barcode identification, speeding the barcode image acquisition and processing challenges, as well as the defect of low accuracy. We proposed a barcode recognition framework based on AM5728 embedded system, which employed industrial CCD to scan the barcode image, moreover, integrated with AM5728 visual development platform to manipulate the collected images. After that, decoding information is yielded from series of algorithms refer to convolution filtering, barcode positioning as well as recognition facilitated by AM5728 visual development platform. Experimental outcomes validated that the accuracy of our system recognition rate can reach up to satisfied 100% in the threshold condition, with 20 frames per second barcode images recognition rate.
    VL  - 4
    IS  - 6
    ER  - 

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Author Information
  • Color & Image Vision Lab, Yunnan Normal University, Kunming, China

  • Color & Image Vision Lab, Yunnan Normal University, Kunming, China

  • Color & Image Vision Lab, Yunnan Normal University, Kunming, China

  • Color & Image Vision Lab, Yunnan Normal University, Kunming, China

  • Color & Image Vision Lab, Yunnan Normal University, Kunming, China

  • Color & Image Vision Lab, Yunnan Normal University, Kunming, China

  • Institute of Electronic Science and Engineering, Nanjing University, Nanjing, China

  • Color & Image Vision Lab, Yunnan Normal University, Kunming, China

  • Color & Image Vision Lab, Yunnan Normal University, Kunming, China

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