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The Development of Diseases Identification System in Paddy Plant Using Image Processing Technique
Author(s) -
Alex Wenda,
Nanda Putri Miefthawati,
Mas’ud Zein
Publication year - 2019
Publication title -
proceeding international conference on science and engineering
Language(s) - English
Resource type - Journals
ISSN - 2598-232X
DOI - 10.14421/icse.v2.92
Subject(s) - identification (biology) , computer science , usability , segmentation , plant disease , image processing , software , image segmentation , artificial intelligence , simplicity , pattern recognition (psychology) , computer vision , image (mathematics) , microbiology and biotechnology , biology , human–computer interaction , botany , programming language , philosophy , epistemology
There are three types of paddy leaf disease that have similar symptoms, making it difficult for farmers to identify them, namely Blast Disease, Brown-Spot Disease, and Narrow Brown-Spot Disease. This paper aims to develop an application to identify paddy leaf disease automatically. Several important aspects of the development of software engineering such as usability, interactivity, and simplicity have been considered. Image processing techniques, namely Blobs analysis and color segmentation are used to get the characteristics of diseased leaf; these characteristics are then used to identify the type of diseases using a rule-based expert system. The results obtained indicate that the developed system recognition capability is considered satisfactory with an accuracy of 94.7%.

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