A New Algorithm for Feature Extraction of Plant Diseases and Insect Pests Signal Based on Optimal Wavelet Packet and Non-negative Matrix Factorization

Abstract

Plant diseases and insect pests have similar symptoms, but it is difficult to distinguish between professional and technical personnel to identify plant diseases and insect pests. In order to accurate extraction of plant diseases and insect pests, physiological and pathological characteristics of signal, puts forward a based on lifting wavelet transform feature extraction algorithm optimization scheme, for the study of plant diseases and insect pests damage signal showing the effect of the prior farmers identify any disease, choose the correct method of governance, quickly make the right decision, improve farmers plant diseases and insect pests, harm signal feature extraction and recognition level. The simulation results show that this algorithm can be used to optimize the stability and convergence, and can be used as an ideal plant disease and insect pests signal feature extraction optimization algorithm, which can effectively identify the different plant diseases and insect pests.