华中科技大学学报：自然科学版2012，Vol.40Issue(7)：57-61,5.
生产线复杂场景条件下的动目标提取方法
Approach to extract moving targets from production line under complex scenes
摘要
Abstract
For billet extraction in steel heavy rail production process of billet detection,an improved interactive graph cuts method was proposed.First the labeled seeds were accurately classified using an improved K-means clustering algorithm based on color divergence,and then objects from image were divided by an improved graph cuts algorithm.Finally the edge was corrected and the noise was removed.Experiment results show that this algorithm can make full use of the characteristics of region and boundary of images improving the speed and quality of segmentation,and the segmentation result can meet the need of practical application.关键词
图像分割/复杂场景/钢坯提取/图论/K均值聚类/最大流/最小割Key words
image cut/complex scene/billet extraction/graph theory/K-means clustering/maxflow/min-cut分类
信息技术与安全科学引用本文复制引用
洪汉玉,颜露新,郭祥云,俞喆俊..生产线复杂场景条件下的动目标提取方法[J].华中科技大学学报：自然科学版,2012,40(7):57-61,5.基金项目
国家自然科学基金资助项目 （）
武汉市科技攻关项目 （）
湖北省自然科学基金资助项目 （）
武汉市学科带头人计划资助项目 （）
