Application of Support Vector Machine for Detecting Rice Diseases Using Shape and Color Texture Features

Autor:	Yang Hu, Zexin Guan, Yang Baojun, Yingfeng Zhou, Jian Tang, Qing Yao
Rok vydání:	2009
Předmět:	Artificial neural network Spots business.industry Computer science fungi Feature extraction information science food and beverages Pattern recognition Image processing Image segmentation Object detection Support vector machine Blight Computer vision Artificial intelligence business
Zdroj:	2009 International Conference on Engineering Computation.
DOI:	10.1109/icec.2009.73
Popis:	For detecting rice disease early and accurately, we presented an application of image processing techniques andSupport Vector Machine (SVM) for detecting rice diseases.Rice disease spots were segmented and their shape and texture features were extracted. The SVM method was employed to classify rice bacterial leaf blight, rice sheath blight and rice blast. The results showed that SVM could effectively detect and classify these disease spots to an accuracy of 97.2%.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::923134e9f56ec2550699d35efe5ff037 https://doi.org/10.1109/icec.2009.73 Zobrazit plný text záznamu