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Open AccessArticle

Peach Flower Monitoring Using Aerial Multispectral Imaging

1
Department of Physics and Engineering, Northwest Nazarene University, Nampa, ID 83686, USA
2
Parma Research and Extension Center, University of Idaho, Parma, ID 83660, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Gonzalo Pajares Martinsanz and Francisco Rovira-Más
J. Imaging 2017, 3(1), 2; https://doi.org/10.3390/jimaging3010002
Received: 25 October 2016 / Revised: 27 December 2016 / Accepted: 29 December 2016 / Published: 6 January 2017
(This article belongs to the Special Issue Image Processing in Agriculture and Forestry)
One of the tools for optimal crop production is regular monitoring and assessment of crops. During the growing season of fruit trees, the bloom period has increased photosynthetic rates that correlate with the fruiting process. This paper presents the development of an image processing algorithm to detect peach blossoms on trees. Aerial images of peach (Prunus persica) trees were acquired from both experimental and commercial peach orchards in the southwestern part of Idaho using an off-the-shelf unmanned aerial system (UAS), equipped with a multispectral camera (near-infrared, green, blue). The image processing algorithm included contrast stretching of the three bands to enhance the image and thresholding segmentation method to detect the peach blossoms. Initial results showed that the image processing algorithm could detect peach blossoms with an average detection rate of 84.3% and demonstrated good potential as a monitoring tool for orchard management. View Full-Text
Keywords: blossoms; digital image processing; machine vision; peaches; unmanned aerial system blossoms; digital image processing; machine vision; peaches; unmanned aerial system
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MDPI and ACS Style

Horton, R.; Cano, E.; Bulanon, D.; Fallahi, E. Peach Flower Monitoring Using Aerial Multispectral Imaging. J. Imaging 2017, 3, 2.

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