At early growth stages: Machine vision-based automated corn plant population and spacing measurement

L. Tang, B. L. Steward, Lei Tian, D. S. Shrestha

Research output: Contribution to journalShort survey

Abstract

Researchers from Iowa State University (ISU) and the University of Illinious have developed a real-time machine vision system to automate the measurement processes of plant population and spacing for corn plants at early growth stage. The key technology involved in the development of the system is video image processing as crop rows are remotely sensed by a video camera. Image processing algorithms have been developed to optimize the performance and computational efficiency of video frame sequencing and plant identification. The plant population and spacing sensing system is capable to perform real-time video analysis at travel speeds up to 4mph.

Original languageEnglish (US)
Number of pages1
JournalResource: Engineering and Technology for Sustainable World
Volume12
Issue number7
StatePublished - Sep 1 2005

ASJC Scopus subject areas

  • Biotechnology
  • Agricultural and Biological Sciences(all)
  • Engineering(all)

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