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Assessment of weed density at an early stage by use of image processing

Assessment of weed density at an early stage by use of image processing Summary Identification of plants against a soil background using colour images is discussed, and a technique is presented for finding plant segments consisting of crop or weed plants, or both. The problems of overlapping plants and image border effects are explored using techniques developed in stereology. An automatic weed density estimation method is proposed, based on a non–linear regression model and features of the plant segments in an image. The method is applied to a set of images from five barley fields. At present two features of the segments are used: segment area and whether a segment cuts the image border or not. Further, a method is suggested for evaluating the automatic weed density estimation by comparison with an interactive weed density estimator including human judgement. Critical factors and ways of improving the automatic method by including additional features are discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Weed Research Wiley

Assessment of weed density at an early stage by use of image processing

Weed Research , Volume 37 (1) – Feb 1, 1997

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References (13)

Publisher
Wiley
Copyright
Copyright © 1997 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0043-1737
eISSN
1365-3180
DOI
10.1111/j.1365-3180.1997.tb01817.x
Publisher site
See Article on Publisher Site

Abstract

Summary Identification of plants against a soil background using colour images is discussed, and a technique is presented for finding plant segments consisting of crop or weed plants, or both. The problems of overlapping plants and image border effects are explored using techniques developed in stereology. An automatic weed density estimation method is proposed, based on a non–linear regression model and features of the plant segments in an image. The method is applied to a set of images from five barley fields. At present two features of the segments are used: segment area and whether a segment cuts the image border or not. Further, a method is suggested for evaluating the automatic weed density estimation by comparison with an interactive weed density estimator including human judgement. Critical factors and ways of improving the automatic method by including additional features are discussed.

Journal

Weed ResearchWiley

Published: Feb 1, 1997

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