Research On Maize Diseases Intelligent Diagnosis Based On Disease Images

The paper took maize disease image for main materials, variety of users'requirements for guide to explore new solutions for identifying diseases with disease images. This study investigated technologies of corn leaf spot diseases automatic diagnosis by using digital image processing, fussy theory and pattern recognition, and constructed the'Expert System For the Diagnosis of Corn Diseases' by using expert system, artificial intelligence and Network Information technology, The main contents are as followings:1. Selection of Image segmentation Algorithms. Algorithm of Middle filter was used to eliminate noise, and algorithm of image sharpening was used to enhance images. Afterward, Gauss-MRF model and seeded regional growing algorithm were realized and introduced to segment corn spot disease images, and these algorithms were compared with representative algorithm used to segment crop disease image in the past. Finally seeded regional growing algorithm was selected.2. Character extraction and selection. Primarily extracted 14 characteristic value from monochrome color, texture and geometry shape on Processed disease image, and then optimized and selected these characteristic value, finally got circularity, eccentricity and rectangle 3 representative characteristic parameter.3. Diseases automatic identification and diagnosis. Use fuzzy pattern recognition to classify the corn disease images, studied membership principle identification and closest principle identification, designed corresponding classifier, and built disease diagnostic model. Took Visual C 6.0 as the tool, compiled the program code, finally feasible software was formed.4. Construction of corn diseases diagnosis expert system based on image rule. Based on in-depth analysis of diagnosis and preventive treatment knowledge of corn diseases, the authors have developed the 'Expert System for Diagnosis of Corn Diseases'with friendly interface, easy expandability and practicability, which is designed as specific to agro-technicians at grass-root level and farmers users on the ground that it features human-computer interaction on actual images of typical characteristic facts in the fields, provides multi-service on the basis of both network system and stand-alone software. The system has been expanded and applied in the national scope through National Corn Industry Technique System.