Identification of Various Plant Leaf Diseases Based on Multi-feature BP Neural Network
In order to accurately identify the health status of plants and better manage the health of plants,this study took healthy and diseased leaves of pomegranate,lemon and mango plants as the research objects,and designed BP neural network model to identify the health status of plants.Firstly,the color and shape features of plant leaves were extracted,then the texture features of plant leaves were extracted by wavelet transform,and the dimension of extracted feature data was reduced by PCA method.Secondly,BP neural network model was established to classify and recognize plants.The recognition accuracy of different feature combinations was up to 83.9％.The BP neural network based on color,shape and texture features has the best recognition effect,and can identify the disease of various plant leaf conveniently and efficiently.
leaves of plantsdisease identificationfeature extractionprincipal component analysis(PCA)BP neural network
NETL
NSTL
万方数据
