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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)

Abstract

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.

Keywords

  • 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.

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  • DOI: 10.1007/978-3-540-71457-6_36
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References

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© 2007 Springer Berlin Heidelberg

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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. https://doi.org/10.1007/978-3-540-71457-6_36

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  • DOI: https://doi.org/10.1007/978-3-540-71457-6_36

  • 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)