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

Comments

This article was originally published as: 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. Original article available here

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.

Share

 
COinS