Classification of Bidens in wheat farms. (19th August 2010)

• Record Type: Journal Article
• Authors: Zhang, Zhengzhi; Kodagoda, Sarath; Ruiz, David; Katupitiya, Jayantha; , Gamini Dissanayake
• Is Part Of: International journal of computer applications technology. Volume 39:Number 1-3(2010)
• Page Start: 123
• Page End: 129
• Publication Date: 2010-08-19
• Subjects: weed detection -- classification -- sensing -- precision agriculture -- Bidens pilosa L -- cobbler&#39 -- s peg -- wheat farms -- automatic detection -- colour-based segmentation -- shape-based validation; Technology -- Data processing -- Periodicals; 620.00285
• Languages: English
• ISSNs: 0952-8091

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%.