高电压技术2018，Vol.44Issue(8)：2525-2532,8.DOI:10.13336/j.1003-6520.hve.20180731012
基于改进C-V模型的外绝缘放电紫外图像特征量提取
Ultraviolet Image Parameters Extraction of Insulation Surface Discharge Based on Improved C-V Model
摘要
Abstract
To segment the discharge area of insulator in ultraviolet (UV) image produced by ultraviolet imaging technology automatically and accurately, we proposed an improved method based on an improved Chan-Vese (C-V) model to analyze the discharge area, where the existing C-V model is improved by adding a penalized energy term, displacing the Dirac function with the norm of level set function gradient, and simplifying amount of parameters. Then, the method was used to obtain the discharge spot of the ultraviolet image of the insulator surface, and the UV image segmentation results based on the conventional edge detection algorithm and mathematical morphology were also given. The research results indicate that the proposed method can segment the discharge area faster and more accurately with stronger anti-interference ability. The accuracy of the improved C-V model is 5％ higher than that of current methods, and the dependency on key parameters is lower. The proposed C-V model is excellent for segmentation of ultraviolet image parameters. The research results can provide an important reference for the effective detection of the insulation for the transmission line.关键词
边缘检测/C-V模型/放电区域/光斑面积/图像分割/外绝缘/紫外成像Key words
edge detection/C-V model/discharge area/facular area/image segmentation/external insulation/UV imaging引用本文复制引用
王丰华,刘国坚,张宏钊,黄荣辉,刘亚东..基于改进C-V模型的外绝缘放电紫外图像特征量提取[J].高电压技术,2018,44(8):2525-2532,8.基金项目
国家自然科学基金(51307109).Project supported by National Natural Science Foundation of China(51307109). （51307109）
