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
fDate :
July 31 2012-Aug. 2 2012
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;
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on
Conference_Location :
GuiLin
Print_ISBN :
978-1-4673-2217-1
DOI :
10.1109/ICDMA.2012.217
