Barcode Recognizable System Implementing Based on AM5728

Xicai Li; Junsheng Shi; Xiaoqiao Huang; Yonghang Tai; Chongde Zi; Huan Yang; Xingyu Yang; Zhiwei Deng; Feiyan Li

doi:doi:10.11648/j.acis.20160406.12

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Barcode Recognizable System Implementing Based on AM5728

Xicai Li, Junsheng Shi, Xiaoqiao Huang, Yonghang Tai, Chongde Zi, Huan Yang, Xingyu Yang, Zhiwei Deng, Feiyan Li

Published in Automation, Control and Intelligent Systems (Volume 4, Issue 6)

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.

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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

Xicai Li

Color & Image Vision Lab, Yunnan Normal University, Kunming, China
Junsheng Shi

Color & Image Vision Lab, Yunnan Normal University, Kunming, China
Xiaoqiao Huang

Color & Image Vision Lab, Yunnan Normal University, Kunming, China
Yonghang Tai

Color & Image Vision Lab, Yunnan Normal University, Kunming, China
Chongde Zi

Color & Image Vision Lab, Yunnan Normal University, Kunming, China
Huan Yang

Color & Image Vision Lab, Yunnan Normal University, Kunming, China
Xingyu Yang

Institute of Electronic Science and Engineering, Nanjing University, Nanjing, China
Zhiwei Deng

Color & Image Vision Lab, Yunnan Normal University, Kunming, China
Feiyan Li

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

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Plain Text BibTeX RIS

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}
}

Copy | Download

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  -

Copy | Download