Image Recognition of Maize Diseases Based on Fuzzy Clustering and Support Vector Machine Algorithm

被引：3

作者：

Chen, Guifen ^{[2
]}

Hu, Jing ^{[2
]}

Li, Daoliang ^{[1
]}

Si, Xiuli ^{[2
]}

机构：

[1] China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China

[2] Jilin Agr Univ, Coll Informat Technol, Changchun 130118, Jilin, Peoples R China

来源：

SENSOR LETTERS | 2012年 / 10卷 / 1-2期

关键词：

Support Vector Machine; Fuzzy Clustering; Image Processing; Identification of Maize Diseases;

D O I：

10.1166/sl.2012.1882

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

As to the fact that recognition rate of maize diseases is not high enough, this paper aims to find a new method used for recognize maize disease in ways of fuzzy cluster and vector machine based on machine vision technology. Enhance images with median filter method, and divide disease with the method of fuzzy c-means clustering algorithms, then extract color, shape, and texture feature. Finally, recognize disease with SVM recognition method, and the recognition accuracy rate is above 95%. Median filter algorithm could be used to smooth disease images of maize effectively. Meanwhile segmentation algorithm of fuzzy cluster could divide disease images of maize accurately, especially it is better that make use of SVM linear kernel function identifying these images as classified function.

引用

页码：433 / 438

页数：6