Gall mite inspection on dormant black currant buds using machine vision

M.R. Nielsen; M.S. Laursen; M.S. Jonassen; K. Nielsen; R.N. Jørgensen

Gall mite inspection on dormant black currant buds using machine vision

In: Precision agriculture '13

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M.R. Nielsen

M.R. Nielsen ¹Danish Technological Institute, Robot Technology, Forskerparken 10F, 5230 Odense, Denmark; mlnn@dti.dk

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M.S. Laursen

M.S. Laursen ²University of Southern Denmark, Niels Bohr Alle 1, 5230 Odense, Denmark

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M.S. Jonassen

M.S. Jonassen ¹Danish Technological Institute, Robot Technology, Forskerparken 10F, 5230 Odense, Denmark; mlnn@dti.dk

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K. Nielsen

K. Nielsen ¹Danish Technological Institute, Robot Technology, Forskerparken 10F, 5230 Odense, Denmark; mlnn@dti.dk

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R.N. Jørgensen

R.N. Jørgensen ²University of Southern Denmark, Niels Bohr Alle 1, 5230 Odense, Denmark

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Type:: Chapter

Pages:: 515–524

DOI:: https://doi.org/10.3920/9789086867783_065

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This paper presents a novel machine vision-based approach detecting and mapping gall mite infection in dormant buds on black currant bushes. A vehicle was fitted with four cameras and RTK-GPS. Results compared automatic detection to human decisions based on the images, and by mapping the results into the same GPS map as the original ground truth recorded in the field. Human inspection found 52% of the infected bushes and the algorithm found the same 52%. The algorithm marked 7% of the healthy bushes, due to healthy buds looking larger closer to the camera. Consequently, the remaining challenge lies in optimising the viewing perspective.

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Precision agriculture '13

E-Book ISBN:: 9789086867783

Publisher:: Wageningen Academic

Print Publication Date:: 01 Nov 2013

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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Gall mite inspection on dormant black currant buds using machine vision

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Precision agriculture '13

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