Identification of Maize Leaf Diseases Cause by Fungus with Digital Image Processing (Case Study : Bismarak Village Kupang District - East Nusa Tenggara)

被引：0

作者：

Overbeek, Marlinda Vasty ^{[1
]}

Kaesmetan, Yampi R. ^{[2
]}

Tobing, Fenina Adline Twince ^{[1
]}

机构：

[1] Univ Multimedia Nusantara Tangerang, Fac Tech & Informat, Study Program Informat, Banten, Indonesia

[2] STIKOM Uyelindo Kupang, Study Program Informat Tech, Kupang, East Nusa Tengg, Indonesia

来源：

PROCEEDINGS OF 2019 5TH INTERNATIONAL CONFERENCE ON NEW MEDIA STUDIES (CONMEDIA 2019) | 2019年

关键词：

digital image processing; maize leaf diseases cause by fungus; Sobel operator; multiclass Support Vector Matrix; Radial Basis Function kernel; shape feature extraction;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Characteristics in common disease caused by a fungus often makes farmers wrong in giving treatment. Prevention is given too often wrong because it is by direct observation. Therefore in this study, we propose a system to detect disease in maize leaf caused by fungi with a view of segmentation or the shape of the maize leaf-based on digital image processing. The sobel operator we used as a shape features extraction. As for the detection technique, we used multiclass Support Vector Machine algorithm with Radial Basis Function kernel. The results of the identification accuracy of the system are 92 225%.

引用

页码：125 / 128

页数：4