华中科技大学学报（自然科学版）2018，Vol.46Issue(1)：63-66,86,5.DOI:10.13245/j.hust.180113
基于改进CV模型的目标多色彩图像分割
Multi-color object image segmentation based on improved CV model
摘要
Abstract
As Chan-Vese(CV) model could not fully segment the image of object color are diversity and mutability,thus an improved CV model was proposed.The internal pixels of image evolution contours were processed by K-means clustering,and the clustering center point values were obtained.The internal fitting values of CV model was constructed by the clustering center point values and the image mean filtered intensity information,thereby improving the adaptability of CV model for complex object image segmentation.In addition,rectangular Dirac function was used to replace regularized Dirac function in the energy function of CV model,and the calculation of level set evolution equation could be limited to the zero level set so as to avoid the influence of the image background disturbance on the segmentation result.The experimental result shows that the improved CV model can accurately and quickly segment the multi-color and color-mutation object image.关键词
高原鼠兔/Chan-Vese(CV)模型/图像分割/K-means聚类/均值滤波Key words
ochotona curzoniae/Chan-Vese (CV) model/image segmentation/K-means clustering/mean filter分类
信息技术与安全科学引用本文复制引用
张爱华,王帆,陈海燕..基于改进CV模型的目标多色彩图像分割[J].华中科技大学学报（自然科学版）,2018,46(1):63-66,86,5.基金项目
国家自然科学基金资助项目(61362034,81360229) （61362034,81360229）
甘肃省高等学校科研资助项目(2016B-025) （2016B-025）
甘肃省基础研究创新群体项目(1506RJIA031). （1506RJIA031）
