哈尔滨工程大学学报Issue(7)：857-864,8.DOI:10.3969/j.issn.1006-7043.201309067
改进的分水岭图像分割算法
Image segmentation algorithm based on the improved watershed algorithm
摘要
Abstract
An improved watershed image segmentation algorithm based on particle swarm and region growing was proposed to solve the problems of noisesensitivity and over-segmentation. The improved algorithm, combining region growing with the classical watershed algorithm, was established by constructing an objective function based on Shannon entropy to determine the parameter of the region growing. The regional disparity degree was calculated by the gray mean, and the smaller region was merged with the neighbor region with a minimal disparity degree. The particle swarm optimization algorithm was employed to search the global optimization of the objective function. Ex-perimental results show that this improved algorithm is better than other image segmentation methods, and can solve effectively the problem of over-segmentation that existed with the watershed algorithm. The segmentation results con-form to the visual characteristics of the human eye, so this algorithm is therefore an effective, accurate, and practi-cal image segmentation method.关键词
图像分割/数学形态学/分水岭算法/区域生长/粒子群算法/过分割/香农熵Key words
image segmentation/mathematical morphology/watershed algorithm/region growing/particle swarm optimization/over-segmentation/Shannon entropy分类
信息技术与安全科学引用本文复制引用
孙惠杰,邓廷权,李艳超..改进的分水岭图像分割算法[J].哈尔滨工程大学学报,2014,(7):857-864,8.基金项目
国家自然科学基金资助项目（41071262，41101243）；哈尔滨师范大学预研基金资助项目（11XY-03）． （）
