DocumentCode
3300041
Title
The Identification System of Wheat Pests Based on PCA and SVM
Author
Jian, Li ; Lijuan, Wang ; Yi, Li
Author_Institution
Shaanxi Univ. of Sci. & Technol., Xi´´an, China
fYear
2012
fDate
July 31 2012-Aug. 2 2012
Firstpage
919
Lastpage
921
Abstract
An identification system of wheat pests is established by the combination of PCA (Principal Component Analysis) and SVM (Support Vector Machine) in this paper. Here PCA is used to extract image features on the wheat pests and SVM is used to identify classification on the feature vectors. It is shown that the system can get better identification efficiency, which can reach an identification rate of 81.25%. The effectiveness of this method is verified by MATLAB simulation experiments.
Keywords
agricultural safety; biology computing; feature extraction; image classification; pest control; principal component analysis; support vector machines; MATLAB simulation; PCA; SVM; feature vectors; identification efficiency; image classification; image feature extraction; principal component analysis; support vector machine; wheat pest identification system; Educational institutions; Feature extraction; Principal component analysis; Production; Reactive power; Support vector machines; Training; PCA; SVM; wheat pests;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on
Conference_Location
GuiLin
Print_ISBN
978-1-4673-2217-1
Type
conf
DOI
10.1109/ICDMA.2012.217
Filename
6298666
Link To Document