On-the-go machine vision sensing of cotton plant geometric parameters: first results

McCarthy, Cheryl and Hancock, Nigel and Raine, Steven R. (2006) On-the-go machine vision sensing of cotton plant geometric parameters: first results. In: 13th Annual Conference on Mechatronics and Machine Vision in Practice, 5-7 Dec 2006, Toowoomba, Australia.

Abstract

[Abstract]: Plant geometrical parameters such as internode length (i.e. the distance between successive branches on the main stem) indicate water stress in cotton. This paper describes a machine vision system that has been designed to measure internode length for the purpose of determining real-time cotton plant irrigation requirement. The imaging system features an enclosure which continuously traverses the crop canopy and forces the flexible upper main stem of individual plants against a glass panel at the front of the enclosure, hence allowing images of the plant to be captured in a fixed object plane. Subsequent image processing of selected video sequences enabled detection of the main stem in 88% of frames. However, node detection was subject to a high false detection rate due to leaf edges present in the images. Manual identification of nodes in the acquired imagery enabled measurement of internode lengths with 3% standard error.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Author's version deposited in accordance with the copyright policy of the publisher. Full conference proceedings held in disk format in USQ Library at call no. AV 629.89 Con.
Depositing User: epEditor USQ
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - No Department
Date Deposited: 11 Oct 2007 00:59
Last Modified: 02 Jul 2013 22:42
Uncontrolled Keywords: plants, cotton, geometrical parameters, geometric parameters, machine vision system, machine vision sensing
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080104 Computer Vision
09 Engineering > 0910 Manufacturing Engineering > 091007 Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics)
URI: http://eprints.usq.edu.au/id/eprint/2214

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