Classification of Bidens in wheat farms Online publication date: Wed, 18-Aug-2010
by Zhengzhi Zhang, Sarath Kodagoda, David Ruiz, Jayantha Katupitiya, Gamini Dissanayake
International Journal of Computer Applications in Technology (IJCAT), Vol. 39, No. 1/2/3, 2010
Abstract: Bidens pilosa L. (commonly known as cobbler's peg) is an annual broad leaf weed widely distributed in tropical and subtropical regions of the world and is reported to be a weed of 31 crops, including wheat. Automatic detection of Bidens in wheat farms is a non-trivial problem due to their similarity in colour and presence of occlusions. This paper proposes a methodology which could be used to discriminate Bidens from wheat to be used in operations such as autonomous weed destruction. A spectrometer is used to analyse the optical properties of Bidens and wheat leaves while achieving high classification results. However, due to the practical constraints of using spectrometers, a colour camera-based technique is proposed. It is shown that the colour-based segmentation followed by shape-based validation algorithm gives rise to high detection rates with lower false detections. We have experimentally evaluated the algorithm with Bidens detection rate of 80% and a false alarm rate of 10%.
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