The Identification System of Wheat Pests Based on PCA and SVM

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.