Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/108565
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Type: Conference paper
Title: Study on spike detection of cereal plants
Author: Qiongyan, L.
Cai, J.
Berger, B.
Miklavcic, S.
Citation: Proceedings of the 2014 13th International Conference on Control Automation Robotics and Vision, 2014 / pp.228-233
Publisher: Institute of Electrical and Electronics Engineers Inc.
Issue Date: 2014
Series/Report no.: International Conference on Control Automation Robotics and Vision
ISBN: 9781479951994
ISSN: 2474-2953
Conference Name: 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV 2014) (10 Dec 2014 - 12 Dec 2014 : Singapore, Singapore)
Statement of
Responsibility: 
Li Qiongyan, Jinhai Cai, Bettina Berger, Stan Miklavcic
Abstract: The spike of a cereal plant is the grain-bearing organ whose physical properties are therefore critical components for plant yield. The ability to detect spikes from 2D images of cereals, such as wheat, provides vital information on tiller number and plants yield potential. We propose a novel spike detection method, which uses both RGB and fluorescence images. Firstly, an improved colour index method is used in the segmentation of plant feature from visible light RGB images, while threshold colour segmentation is applied to fluorescence images. Secondly, morphology algorithms are used to refine the initial segmentation results. Thirdly, a neural network-based method using Laws texture energy is performed for spike detection; connected and overlapping spikes are identified based on the average area and average perimeter of spikes and separated by a straight line through the center of the overlapping region. Finally, the spikes are extracted using area and height thresholds. Experimental results with two data sets have shown that the proposed method is simple, practical and can identify spikes with an accuracy of over 80%.
Keywords: Wheat spike detection, segmentation, colour indices, Laws texture energy , overlapped spike detection and separation
Rights: © 2014 IEEE
RMID: 0030027834
DOI: 10.1109/ICARCV.2014.7064309
Appears in Collections:Agriculture, Food and Wine publications

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