Research And Application Of Maize Leaf Disease Fuzzy Recognition Method Based On Image Characteristics

Along with increasing ability of computer process as well as rapid development of image processing and recognition technology, this technology not only is applied to agriculture more and more widely, but also is an important technology to achieve agriculture information and automation. The amount of work for gathering agriculture information is tremendous; besides the realtime and accuracy of information are widely paid attention to in agriculture production and scientific research. How to diagnose disease of crops timely and accurately is always an important part of research facing to the agriculture field through computer technology. At the same time crop disease, insect pest and weed affect the output and quality of crop badly. The paper mainly aimed at the problem of low precision and untimely diagnosis about crop disease, by means of computer image processing technology as an important means, took common maize leaf diseases as study object and brought forward feasible method to improve diagnosis precision applying the knowledge on image processing and plant physiology synthetically, therefore it provides theory to the correlative research of auto recognition and diagnosis of crop disease, insect pest and weeds.The paper represented the theory of image processing and recognition, made use of VC++ programming language build up the recognition software system and project team built the hardware system to get the diseases image. According to the characteristics of maize leaf disease, TSRG method was adopted to segment the disease image; area-marking and Freeman link code method were used calculating the num of disease well as wiping off redundancy dots. And then extracted the disease spot's color and form feature and saved in the database. Based on fuzzy decision making and mean of maximum method, Fuzzy Recognition algorithm was used to recognize six kinds of maize leaf disease. The paper integrated the results of other recognition methods, which were used to research crops, and got the effective identification of diagnostic results, which provides software and technology support for crops'diseases, pests and weeds diagnosis and recognition research.The study made two aspects of progress in the following. First, it realized automatic identification of the common six kinds of maize leaf disease, and the recognition accuracy rate of over 90%. Secondly, the paper analysised the feature of the maize leaf disease and selected the features which made a greater contribution to recognition; at the same time, Fuzzy Recognition algorithm adopted to maize leaf disease recognition was a great breakthrough for crops Recognition Research. Because of it integrated the advantages of the other methods and got the identification of diagnostic results, it improved the accuracy and reliability of recognition.The research applied computer vision technology in maize disease recognition, which extends the application area of machine vision and also provide a use for reference in the field of agriculture technology for machine vision.