Research on video image recognition technology of maize disease based on the fusion of genetic algorithm and simulink platform

0Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

This article is free to access.

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.

Cite

CITATION STYLE

APA

Cao, L., Meng, Y., Lu, J., & Chen, G. (2016). Research on video image recognition technology of maize disease based on the fusion of genetic algorithm and simulink platform. In IFIP Advances in Information and Communication Technology (Vol. 479, pp. 76–91). Springer New York LLC. https://doi.org/10.1007/978-3-319-48354-2_8

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free