Recognition of Empoasca Flavescens based on PCA-LDA-SVM algorithm
In order to solve the efficiency and accuracy of Empoasca Flavescens recognition,a recognition method based on PCA-LDA-SVM is proposed.Firstly,the collected tea image are preprocessed and the scaled image is obtained.Then,Principal Component Analysis(PCA)is used to extract global features from the preprocessed image to reduce the dimension of feature data,so as to reduce the subsequent calculation time.Linear Discriminant Analysis(LDA)is used to find the optimal projection space of feature data to minimize the intra class dispersion distance and maximize the inter class dispersion distance,so as to further improve precision and accuracy of recognition.Finally,Support Vector Machine(SVM)classifier is used for classification and recognition.The experimental results show that the recognition accuracy of PCA-LDA-SVM model can reach 96%,precision can reach 100%,and recall can reach 92%.The overall recognition performance is better than that of SVM,BP,KNN,PCA-SVM model,which has certain theoretical value and reference significance.
万方数据
维普
