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Weed Recognition Using Image-Processing Technique Based on Leaf Parameters

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Title Weed Recognition Using Image-Processing Technique Based on Leaf Parameters
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Creator Kamal N Agrawal, Karan Singh, Ganesh C Bora, Dongqing Lin
 
Subject Machine vision, weed detection, image-processing, leaf parameters.
 
Description Not Available
Weeds normally grow in patches and spatially distributed in field. Patch spraying to control weeds has advantages of
chemical saving, reduced cost and environmental pollution. Advent of electro-optical sensing capabilities has paved the way of using
machine vision technologies for patch spraying. Machine vision system has to acquire and process digital images to make control
decisions. Proper identification and classification of objects present in image holds the key to make control decisions and use of any
spraying operation performed. Recognition of objects in digital image may be affected by background, intensity, image resolution,
orientation of the object and geometrical characteristics. A set of 16, including 11 shape and 5 texture-based parameters coupled with
predictive discriminating analysis has been used to identify the weed leaves. Geometrical features were indexed successfully to
eliminate the effect of object orientation. Linear discriminating analysis was found to be more effective in correct classification of
weed leaves. The classification accuracy of 69% to 80% was observed. These features can be utilized for development of image
based variable rate sprayer.
Not Available
 
Date 2017-01-08T11:04:41Z
2017-01-08T11:04:41Z
2012
 
Type Research Paper
 
Identifier Not Available
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/1106
 
Language English
 
Relation Not Available;
 
Publisher David Publishing Company