The Research of Disease Spots Extraction Based on Evolutionary Algorithm. (3rd May 2017)

• Record Type: Journal Article
• Authors: Li, Kangshun; Xiong, Lu; Zhang, Dongbo; Liang, Zhengping; Xue, Yu
• Other Names: Gong Maoguo Academic Editor.
• Is Part Of: Journal of optimization. Volume 2017(2017)
• Publication Date: 2017-05-03
• Subjects: Mathematical optimization -- Periodicals; Structural optimization -- Periodicals; Mathematical optimization; Structural optimization; Periodicals; Electronic journals; 519.6
• DOI: 10.1155/2017/4093973
• Languages: English
• ISSNs: 2356-752X

Abstract

Abstract : According to the characteristics of maize disease spot performance in the image, this paper designs two-histogram segmentation method based on evolutionary algorithm, which combined with the analysis of image of maize diseases and insect pests, with full consideration of color and texture characteristic of the lesion of pests and diseases, the chroma and gray image, composed of two tuples to build a two-dimensional histogram, solves the problem of one-dimensional histograms that cannot be clearly divided into target and background bimodal distribution and improved the traditional two-dimensional histogram application in pest damage lesion extraction. The chromosome coding suitable for the characteristics of lesion image is designed based on second segmentation of the genetic algorithm Otsu. Determining initial population with analysis results of lesion image, parallel selection, optimal preservation strategy, and adaptive mutation operator are used to improve the search efficiency. Finally, by setting the fluctuation threshold, we continue to search for the best threshold in the range of fluctuations for implementation of global search and local search.