A Fast and Efficient Shape Descriptor for an Advanced Weed Type Classification Approach
Abstract
In weed management, the distinction between monocots and dicots species is an important issue. Indeed, the yield is much higher with the application of a selective treatment instead of using a broadcast herbicide overall the parcel. This article presents a fast shape descriptor designed to distinguish between these two families of weeds. The efficiency of the descriptor is evaluated by analyzing data with the pattern recognition process known as the discriminant factor analysis (DFA). Excellent results have been obtained in the differentiation between these two weed species
Keywords
Shape descriptor; Machine vision; Real-time image processing; Weed type classification; Precision agriculture.
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PDFDOI: http://doi.org/10.11591/ijece.v6i3.pp1168-1175
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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).