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Influence of weed maturity levels on species classification using machine vision

Published online by Cambridge University Press:  20 January 2017

T. F. Burks,
S. A. Shearer,
J. D. Green and
J. R. Heath
S. A. Shearer
Affiliation:
Department of Biosystems and Agricultural Engineering, University of Kentucky, Lexington, KY 40546-0276
J. D. Green
Affiliation:
Department of Agronomy, University of Kentucky, Lexington, KY 40546-0091
J. R. Heath
Affiliation:
Department of Electrical Engineering, University of Kentucky, Lexington, KY 40546-0046
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Abstract

The environmental effect of weed control systems has stimulated research into new practices for weed control, such as selective herbicide application methods on weed-infested crop areas. This research used the color co-occurrence method (CCM) texture analysis to determine the effects of plant maturity on the accuracy of weed species classification of digitized images. Two different experimental combinations of weed species and maturity level were examined. The weed species evaluated were ivyleaf morningglory, giant foxtail, large crabgrass, and velvetleaf, with soil image sets added to each experiment. One study examined classification accuracies for two weed species at three maturity levels, and the second study examined four weed species at two maturity levels. For each species-maturity level combination, 40 digital images were collected from a manually seeded outdoor plant bed. Digitized images were transformed from the red–green–blue (RGB) color format into hue–saturation–intensity (HSI) format to generate CCM texture feature data. Stepwise variable reduction procedures were used to select texture variables with the greatest discriminant capacity. Then discriminant analysis was used to determine the classification accuracy for the two different experiments. When using HSI texture statistics, discriminant analysis correctly classified weed species within and across maturity levels with an accuracy above 97% for both experimental groups. These image processing algorithms demonstrate potential use for weed scouting, weed infestation mapping, and weed control applications using site-specific farming technology.

Keywords

Ivyleaf morningglory, Ipomoea hederacea (L.) Jacq. IPOHEgiant foxtail, Setaria faberi Hermm. SETFAlarge crabgrass, Digitaria sanguinalis (L.) Scop. DIGSAvelvetleaf, Abutilon theophrasti Medik. ABUTHImage processingweed identificationcolor texture analysissite-specific farmingprecision agriculture

Information

Type
Research Article
Information
Weed Science , Volume 50 , Issue 6 , December 2002, pp. 802 - 811
Copyright
Copyright © Weed Science Society of America 

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