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Open AccessArticle

High Speed Crop and Weed Identification in Lettuce Fields for Precision Weeding

School of Electrical and Electronic Engineering, The University of Manchester, Oxford Rd, Manchester M13 9PL, UK
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Sensors 2020, 20(2), 455; https://doi.org/10.3390/s20020455
Received: 7 November 2019 / Revised: 3 December 2019 / Accepted: 25 December 2019 / Published: 14 January 2020
(This article belongs to the Special Issue Smart Sensing Technologies for Agriculture)
Precision weeding can significantly reduce or even eliminate the use of herbicides in farming. To achieve high-precision, individual targeting of weeds, high-speed, low-cost plant identification is essential. Our system using the red, green, and near-infrared reflectance, combined with a size differentiation method, is used to identify crops and weeds in lettuce fields. Illumination is provided by LED arrays at 525, 650, and 850 nm, and images are captured in a single-shot using a modified RGB camera. A kinematic stereo method is utilised to compensate for parallax error in images and provide accurate location data of plants. The system was verified in field trials across three lettuce fields at varying growth stages from 0.5 to 10 km/h. In-field results showed weed and crop identification rates of 56% and 69%, respectively. Post-trial processing resulted in average weed and crop identifications of 81% and 88%, respectively. View Full-Text
Keywords: precision weeding; multispectral imaging; kinetic stereo imaging; plant detection precision weeding; multispectral imaging; kinetic stereo imaging; plant detection
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Elstone, L.; How, K.Y.; Brodie, S.; Ghazali, M.Z.; Heath, W.P.; Grieve, B. High Speed Crop and Weed Identification in Lettuce Fields for Precision Weeding. Sensors 2020, 20, 455.

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