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《Journal of Zhengzhou University(Natural Science Edition)》 2019-01
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Plant Image Segmentation Model Based on RGB Color Space

LIU Guoqi;DENG Ming;LI Chenjing;Department of Computer and Information Engineering,Henan Normal University;  
To solve the problem of complex background,weak boundary,and connectivity in plant image segmentation,an improved bi-convex fuzzy variational image segmentation model was proposed. Firstly,the color image was divided into two parts by RGB color space model. The target part of the plant image was kept in the original color. The other part was set to the color background with large difference from the target object. The extracted object contour was used as an initial contour. Secondly,the log edge detection operator was used to improve the robustness of noise,and performed the image enhancement on the plant image. Finally,a new segmentation model was proposed based on the blurring fuzzy variational model. The experimental results showed that the average JS value of the method was improved to95. 68%. The accurate extraction of edge contour of the target object in the rosette plant image was realized. It also effectively solved the problem of the complex background and the connectivity between pixels.
【Fund】: 国家自然科学基金项目(U1404603);; 河南省教育厅科学技术重点研究项目(13A520522)
【CateGory Index】: TP391.41
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