Skip to main content

Detection of Wilt by Analyzing Color and Stereo Vision Data of Plant

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNIP,volume 4418)


The importance of information technology and ubiquitous computing are gained in the agricultural area. A remote monitoring tool, namely Field Servers, is developed and used in recent agricultural industries. The Field Server can handle weather data, measuring and taking photo images for analyzing visualized information. However, image data acquired by the Field Server is not adequately used for automatic control in current systems even though the conditions of plants, pests and thieves can be detected from the images. The purpose of this research is to develop an application which controls peripherals on the basis of features extracted from image data. As our first proposal we developed the farmer support system which pours water to wilting plants automatically. In this system, four indicators are used to detect the wilt of plants that have dense or sparse leaves. Two experiments were employed on using plants which are observed by a Field Server located outside. The experimental results prove that we can detect the wilt of plants by use of the proposed system.


  • Ubiquitous Computing
  • Stereo Vision
  • Green Region
  • Apex Angle
  • Distance Image

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-540-71457-6_36
  • Chapter length: 12 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
USD   84.99
Price excludes VAT (USA)
  • ISBN: 978-3-540-71457-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   109.99
Price excludes VAT (USA)


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Ohtani, T., et al.: Web based IPM system for Japanese pear diseases in Japan. III. Weather data acquisition system to estimate leaf wetness duration and scab infection severity. In: The 2001 KSPP International Conference and Annual Meeting. Plant Disease Forecast: Information Technology in Plant Pathology. Program and Abstracts 63 (2001)

    Google Scholar 

  2. Ninomiya, S., et al.: Present Status and Prospective of Agriculture Grid and Its Implementation. In: SICE-ICASE International Joint Conference (2006)

    Google Scholar 

  3. Sasaki, K.: Progress of Field Server with Image Information and Example of Remote Observation. Keisou 45(1), 65–68 (2002)

    Google Scholar 

  4. Hiratou, M.: Farm Information Monitoring by Using Field Server. Agriculture And Gardening 78(1), 182–188 (2003)

    Google Scholar 

  5. Choi, W., Dohi, M., Ishizuka, N.: Development of precision Production Robot for Flower and Vegetable Seeding (Part 1) -Discrimination of Stock Seeding by Image Processing. Journal of the Japanese Society of Agricultural Machinery 66(2), 68–75 (2004)

    Google Scholar 

  6. Tazuke, A., et al.: Extraction of Region from Plant Images for the Automatic Detection of Leaf Wilting. Agricultural Information Research 11(1), 27–40 (2002)

    Google Scholar 


  8. Takizawa, H., et al.: Plant Recognition by Integrating Color and Range Data Obtained Through Stereo Vision. Journal of Advanced Computational Intelligence and Intelligent Informatics 9(6), 630–636 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations


Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2007 Springer Berlin Heidelberg

About this paper

Cite this paper

Mizuno, S., Noda, K., Ezaki, N., Takizawa, H., Yamamoto, S. (2007). Detection of Wilt by Analyzing Color and Stereo Vision Data of Plant. In: Gagalowicz, A., Philips, W. (eds) Computer Vision/Computer Graphics Collaboration Techniques. MIRAGE 2007. Lecture Notes in Computer Science, vol 4418. Springer, Berlin, Heidelberg.

Download citation

  • DOI:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71456-9

  • Online ISBN: 978-3-540-71457-6

  • eBook Packages: Computer ScienceComputer Science (R0)