Research On Sunflower Leaf Disease Image Acquisition And Recognition System Based On Mobile Internet

China is the largest country in the world for planting sunflowers,and sunflower is an important economic crop in China’s agricultural cultivation.With the gradual expansion of the planting area of sunflower,the diseases of sunflower have become increasingly rampant.Therefore,the accurate identification and effective prevention and control of sunflower diseases are extremely important to the economic development in China.The traditional method uses special equipment to collect images of sunflower leaf diseases,and then performs image processing and analysis on the computer,which cannot quickly and easily complete the disease identification.There are great limitations and it is difficult to meet the development needs of modern agriculture.In recent years,with the rapid development of digital image processing technology,computer technology and network technology,the popularity of the Android mobile terminal provides a new platform for the development of the sunflower disease identification system.This article mainly uses the Android system mobile phone to collect images,combined with digital image processing technology,integrates network communication and pattern recognition technology,and carries out research on the image collection and recognition system of sunflower leaf diseases based on mobile internet.Focused on the research of sunflower leaf diseases,sunflower black spot,bacterial leaf spot,powdery mildew and downy mildew were studied.A sunflower leaf disease image acquisition and recognition system based on mobile internet was proposed.First,the user uses the Android mobile terminal to select an image to be recognized,and sends the image from the Android mobile terminal to the server through the TCP/IP network communication protocol.Then,after receiving the image,the server invokes an image recognition algorithm to identify the image.First,image preprocessing: The main purpose of image preprocessing is to remove the interference information in the image,restore and retain useful information,and at the same time enhance the reliability of useful information.Second,image feature extraction: Selecting the feature parameters of the image to be recognized as the feature input vector for disease recognition,which is the only data basis for the diagnosis of the object.Third,image recognition and diagnosis of sunflower leaf diseases: In this paper,SVM algorithm and SIFT algorithm are used to diagnose and identify sunflower diseases,and the recognition result information is obtained.Finally,the server sends the recognition result and the pest treatment method to the Android mobile terminal through the TCP/IP network communication protocol.After the mobile terminal receives the related disease information,the user can perform appropriate processing on the crop according to the disease information and provide the user with timely information.Agricultural guidance.