Document Type
Conference Proceeding
Publisher
Australian Society of Information and Communication Technologies in Agriculture
Faculty
Faculty of Health, Engineering and Science
School
School of Computer and Security Science / eAgriculture Research Group
RAS ID
18467
Abstract
This article describes the use of Cellular Neural Networks (a class of Ordinary Differential Equation (ODE)), Fourier Descriptors (FD) and NaiveBayes Classifier (NBC) for automatic identification of images of plant leaves. The novelty of this article is seen in the use of CNN for image segmentation and a combination FDs with NBC. The main advantage of the segmentation method is the computation speed compared with other edge operators such as canny, sobel, Laplacian of Gaussian (LoG). The results herein show the potential of the methods in this paper for examining different agricultural images and distinguishing between different crops and weeds in the agricultural system.
Access Rights
free_to_read
Comments
Babatunde, O. H., Armstrong, L. , Leng, J. , & Diepeveen, D. (2014). Application of Cellular Neural Networks and Naive Bayes Classifier in Agriculture. Proceedings of Asian Federation for Information Technology in Agriculture. (pp. 63-72). Perth, W.A. Australian Society of Information and C. Available here