Title :
Application of Support Vector Machine for Detecting Rice Diseases Using Shape and Color Texture Features
Author :
Yao, Qing ; Guan, Zexin ; Zhou, Yingfeng ; Tang, Jian ; Hu, Yang ; Yang, Baojun
Author_Institution :
Coll. of Inf. & Electron., Zhejiang Sci-Tech Univ., Hangzhou, China
Abstract :
For detecting rice disease early and accurately, we presented an application of image processing techniques and Support 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%.
Keywords :
agriculture; crops; feature extraction; image colour analysis; image segmentation; object detection; support vector machines; color texture features; feature extraction; image processing techniques; image segmentation; rice bacterial leaf blight; rice blast; rice disease detection; rice sheath blight; shape features; support vector machine; Crops; Diseases; Feature extraction; Image processing; Image segmentation; Microorganisms; Neural networks; Shape; Support vector machine classification; Support vector machines; image processing; rice diseases spots; support vector machine; texture features;
Conference_Titel :
Engineering Computation, 2009. ICEC '09. International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-0-7695-3655-2
DOI :
10.1109/ICEC.2009.73
