Automated estimation of tiller number in wheat by ribbon detection

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Abstract

The advent of high-throughput phenotyping installations signals a need for plant biology to use pattern analysis and recognition techniques, especially when analysis is done via digital images. Such installations also afford an opportunity to computer vision. We describe one such application at the UK National Plant Phenomics Centre, in which historically measurements have been made in a
labour-intensive manual manner. We develop an estimator of tiller number in growing wheat which, when exploiting per-day averaging, temporal interpolation and dynamic programming, delivers measurements of finer-grain and no less accuracy than manually. The approach developed lends itself to reuse for any similar imaging setup, and plants with tillering characteristics similar to wheat. We consider the work a useful exemplar for co-operation between biologists and computer scientists in such installations.
Original languageEnglish
Pages (from-to)637-646
Number of pages10
JournalMachine Vision and Applications
Volume27
Issue number5
Early online date01 Oct 2015
DOIs
Publication statusPublished - Jul 2016

Keywords

  • small grain cereals
  • branching
  • plant development
  • computer vision

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