Author
Mohamad Lihawa
Subject
- Pertanian
Abstract
The research objective is to produce an Android-based expert system software that is capable of detecting pests and diseases in corn plants and is useful in
providing information about symptoms and its control through image processing. This expert system program is processed through digital signal processing
which consists of four (4) main parts, namely preprocessing, color feature extraction, texture feature extraction, and classi????cation. The color feature extraction
method used is The Color Moment as color feature extraction and GLCM (Gray-Level CooOccurrence Matrix) as a texture feature extraction. The classi????cation
method in this system uses K-Means clustering by dividing images into 4 clusters based on the color and texture of image objects. Training data using Multi SVM
(Support Vector Machine) method. The result of this software program is named Corn Expert System (CES) which is installed on the desktop and the Android
Cellphone (HP). This CES system application begins with taking pictures of corn leaves that are attacked by pests and diseases using Android phones by farmers
in corn????elds and sent to the desktop that is operated by the operator at the Agricultural Extension O????ce. Data from the desktop processing is sent back to the
farmer via an android phone. The results of the detection of this CES program for pests, leaf scrapers and rust disease, leaf spot, leaf blight, and froth blight, have
an accuracy level of up to 90%.
Keywords
Corn Expert System (CES), Diseases of Corn Plants
Publisher
PMAS-Arid Agriculture University Rawalpindi-Pakistan
Contributor
-
Publish
2019
Material Type
ARTIKEL
Right
-
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