DocumentCode
2363599
Title
Classification of Bidens in Wheat Farms
Author
Zhang, Zhenhao ; Kodagoda, Sarath ; Ruiz, Daniel ; Katupitiya, Jayantha ; Dissanayake, Gamini
Author_Institution
ARC Centre of Excellence for Autonomous Syst. (CAS), Univ. of Technol., Sydney, NSW
fYear
2008
fDate
2-4 Dec. 2008
Firstpage
505
Lastpage
510
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 nontrivial problem due to their similarity in color 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 analyze the optical properties of Bidens and wheat leaves while achieving high classification results. However, due to the practical constraints of using spectrometers, a color camera based technique is proposed. It is shown that the color 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 10% false alarm rate.
Keywords
crops; image colour analysis; image segmentation; image sensors; object detection; pattern classification; Bidens pilosa L classification; color based segmentation; color camera based technique; wheat farms; Australia; Cameras; Content addressable storage; Costs; Crops; Linear discriminant analysis; Machine vision; Reflectivity; Shape; Spectroscopy;
fLanguage
English
Publisher
ieee
Conference_Titel
Mechatronics and Machine Vision in Practice, 2008. M2VIP 2008. 15th International Conference on
Conference_Location
Auckland
Print_ISBN
978-1-4244-3779-5
Electronic_ISBN
978-0-473-13532-4
Type
conf
DOI
10.1109/MMVIP.2008.4749584
Filename
4749584
Link To Document