Design And Implementation Of Monitoring System For Wheat Take-all Disease Based On UAV Remote Sensing

With the development and application of information technology in agricultural production,the status of crop disease monitoring technology based on image processing has becoming a hot topic.Now through the image processing technology on wheat disease status monitoring and research are concentrated in the field of powdery mildew,leaf rust,stripe rust,less research on the monitoring of take all disease of wheat.This paper use UAV remote sensing acquisition field environment wheat take-all disease image,in the digital image processing technology and fuzzy clustering image segmentation based on,using java web technology to design and realize the wheat take all disease surveillance system.By UAV wheat take-all disease image acquisition,under the guidance of expert opinion to wheat take-all disease grade was divided into four grades,namely H health,mild LH,moderate M,severe S.Firstly,image enhancement,image denoising,and then the image is converted into RGB,HSV,CIE,Lab three different color space extraction,gray statistic feature and color feature of a total of 33 typical components after feature normalization using Genetic Algorithm optimization of feature selection,the final selection of gray statistics feature 3 and 15 color features,using these 18 parameters as the full knowledge of pattern recognition model of space division;to take all of wheat field in the image after preprocessing using Fuzzy C clustering segmentation algorithm for clustering segmentation,the segmentation results as validation samples were identified on the training sample set in 4 different the degree of wheat disease image using the Fuzzy C means clustering algorithm,and then use the method of fuzzy pattern recognition classifier design,finally The classifier is used to identify the samples.For wheat take-all of four different diseases have achieved satisfactory recognition results,average recognition accuracy rate reached 87.8%,indicating that the based on genetic algorithm of feature extraction based on fuzzy recognition classifier design rationality,and the application of fuzzy c-means clustering segmentation algorithm for different disease severity of take all disease of wheat image segmentation of feasibility.Using the Java programming language,My SQL as the underlying data storage,to Tomcat as the application server,Using SSH technology underlying the development,the use of MVC three-tier architecture,the design and implementation of the wheat take all disease surveillance system.System based on B/S mode design,including user management,image management,and image analysis results management,expert advice on management module,provides the users to upload image,user image management,image analysis and results of the query,and other functions.Through the wheat take all disease monitoring system design and implementation of users for remote monitoring of take all disease of wheat disease situation become available for future farmland real-time monitoring system provides technical support.