Research on Video Image Recognition Technology of Maize Disease Based on the Fusion of Genetic Algorithm and Simulink Pl
In order to improve the segmentation accuracy of maize disease leaves with genetic algorithms and reduce segmentation time, this paper proposed a video image recognition technology of maize disease based on the fusion of genetic algorithm and Simulink sim
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Abstract. In order to improve the segmentation accuracy of maize disease leaves with genetic algorithms and reduce segmentation time, this paper proposed a video image recognition technology of maize disease based on the fusion of genetic algorithm and Simulink simulation platform. The technology firstly uses Simulink simulation platform to process the real-time video data captured, including sharpening, segmenting and smoothing, to improve image clarity and quality; Secondly, it uses genetic algorithm to generate optimization model to determine the optimal image of maize diseases; Finally, it fuses genetic algorithms and Simulink platform to analyze and recognize these optimal images. The study results of maize big-spot disease images show that image grey scale values changes after the process of the fused optimal algorithm so that the characteristics of maize diseases are high lightened and the recognition rate of maize disease video image is improved remarkable. The algorithm provides a valid basis for the identification and the diagnosis and treatment of maize disease. Keywords: Maize big-spot disease Simulink platform
Video image
Genetic algorithm
1 Introduction Computer image processing technology is an important component in the field of artificial intelligence, and between man and computer basic theory and application technology provides a specific interface. But the application of image processing technology in agricultural engineering research starts late in our country, mainly in the crop disease diagnosis [1, 2], agricultural product quality detection [3, 4], crop growth status monitoring [5, 6], agricultural crops intelligent classification [7], etc. The present study show that using image processing technology not only can detect, stem diameter, leaf area, leaf circumference petiole Angle of crops such as external growth parameters, can also with the fruit surface color and fruit size to judging the fruit maturity, and crop water lack of fertilizer, and so on and so forth [8]. Computer image processing technology in crop production and research of information collection and has a large amount of information, high speed and high precision of significant characteristics and advantages, and solve some manual measurement is difficult to solve the problem. © IFIP International Federation for Information Processing 2016 Published by Springer International Publishing AG 2016. All Rights Reserved D. Li and Z. Li (Eds.): CCTA 2015, Part II, IFIP AICT 479, pp. 76–91, 2016. DOI: 10.1007/978-3-319-48354-2_8
Research on Video Image Recognition Technology of Maize Disease
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Domestic started relatively late in the image recognition and processing, but the study of foreign theory made certain optimization, also has obtained certain research results. More mature by identifying plants in the static image texture and color features combined with neural network to achieve for the identification of crop nutrient deficiency. Domestic only video image processing technology was applied to road traffic and dynamic video
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