Open AccessAutomatic Rice Leaf Disease Segmentation Using Image Processing Techniques
Author(s) -
K. S. Archana,
Arun Sahayadhas
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.27.17756
Subject(s) - blight , segmentation , image segmentation , oryza sativa , agriculture , computer science , image processing , artificial intelligence , feature (linguistics) , feature extraction , pattern recognition (psychology) , agronomy , image (mathematics) , biology , ecology , biochemistry , linguistics , philosophy , gene
Agriculture productivity mainly depends on Indian economy. Hence, Disease prediction plays a important role in agriculture field. In image analyzing the symptoms is an essential part for feature extraction and classification. However, some of the challenges are still lacking to predict the disease. To meet those challenges, the proposed algorithm focuses on a specific problem to predict the disease from early symptoms. Bacterial Leaf Blight and Brown Spot are a major bacterial and fungal disease respectively in rice (Oryza sativa) crops, it causes yield loss and reduce the grains quality. This research work focused on automatic detection method for image segmentation on rice leaves under wide range of environmental condition for further analysis. Various hybrid techniques for image segmentation and classification algorithms were analyzed and an automatic detection method has been proposed for identifying the specified diseases in rice leaves under different environmental condition.