Skip to main content
SpringerLink
Log in
Book cover

The Proceedings of the Second International Conference on Communications, Signal Processing, and Systems pp 165–170Cite as

Measurement of Rice Growth Based on the Remote Video Images

  • Conference paper
  • First Online:

  • 936 Accesses

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 246))

Abstract

Rice is one of the major crops in our country. Tracking the growth of rice in time with remote monitoring equipment can provide safeguard for production forecast and disease control of the rice. Adopting wireless video transmission module W730 to realize remote video monitoring on rice growth, the experiment could obtain the growth of rice information, and thus will lay a foundation for forecasting rice yield by collecting growth images of rice at different times, preprocessing real-time image data with the MATLAB image processing module, making segmentation of the image with finite difference method, and marking the median-filtered image.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Wenchuan Guo, Xinhua Zhu (2002) Research progress of machine vision technology in grains identification and classification. Cereal & feed industry (6):50–51

    Google Scholar 

  2. Rei JF et al (1991) Computer vision sensing of stress cracks in corn kernels. Trans ASAE 34(5):2226–2244

    Google Scholar 

  3. Majumdar S et al (1999) Classification of bulk samples of cereal grain using machine vision. Agric Eng Res 73:35–47

    Article  Google Scholar 

  4. Tianzhen L, Baiqing Z (2005) Research on rice-quality inspection basing on computer vision technology. Cereal Food Indus 12(4):50–53

    Google Scholar 

  5. Xuemei W, Chengyao Z, Longqin W (2005) Tomato identification technique based on computer vision using MATLAB. Agri Equip Tech 31(4):15–17

    Google Scholar 

  6. Ming S, Yun L, Yiming W (2002) Computer vision based rice chalkiness detection using MATLAB. Trans CSAE 18(4):146–148

    Google Scholar 

  7. Caiyun H, Oshita S, Seo Y, Kawagoe Y, Torii T, Kudoh K, Higuchi T, Do G (2001) Application of 3D-microslicing image processing system in rice quality evaluation. Trans CSAE 17(3):92–95

    Google Scholar 

Download references

Acknowledgments

This work is supported in part by Tianjin agriculture committee Support Project (201003060),The State Science and Technology Commission Spark Program projects (10ZHXHNCO8300).

Author information

Authors and Affiliations

  1. School of Electromechanical Engineering, Tianjin Agricultural University, Jinjing Road 22, 300384, Tianjin, China

    Ruokui Chang, Hua Liu, Yong Wei & Nan Wang

  2. School of horticulture, Tianjin Agricultural University, Jinjing Road 22, 300384, Tianjin, China

    YuanHong Wang

Authors
  1. Ruokui Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hua Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. YuanHong Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yong Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to YuanHong Wang .

Editor information

Editors and Affiliations

  1. College of Physical and Electronic Infor, Tianjin Normal University, Tianjin, People's Republic of China

    Baoju Zhang

  2. College of Physical and Electronic Infor, Tianjin Normal University, Tianjin, People's Republic of China

    Jiasong Mu

  3. College of Physical and Electronic Infor, Tianjin Normal University, Tianjin, People's Republic of China

    Wei Wang

  4. Department of Electrical Engineering, University of Texas at Arlington, Arlington, Texas, USA

    Qilian Liang

  5. School of electronic engineering, University of Electronic Science and Tec, Chengdu, People's Republic of China

    Yiming Pi

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Chang, R., Liu, H., Wang, Y., Wei, Y., Wang, N. (2014). Measurement of Rice Growth Based on the Remote Video Images. In: Zhang, B., Mu, J., Wang, W., Liang, Q., Pi, Y. (eds) The Proceedings of the Second International Conference on Communications, Signal Processing, and Systems. Lecture Notes in Electrical Engineering, vol 246. Springer, Cham. https://doi.org/10.1007/978-3-319-00536-2_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00536-2_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-00535-5

  • Online ISBN: 978-3-319-00536-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation