基于先验知识和区域信息的Snake模型图像分割研究  

Research on Image Segmentation Based on Snake Model of Previous Knowledge and Region Information

作　　者：周昌雄[1] 于盛林[1] 吴陈[2] 

机构地区：[1]南京航空航天大学自动化学院,南京210016 [2]江苏科技大学电子信息学院,镇江212003

出　　处：《模式识别与人工智能》2006年第2期257-261,共5页Pattern Recognition and Artificial Intelligence

基　　金：江苏省教育厅自然科学基金项目(No.2002316);江苏省社会发展项目(No.2005DX015J)资助

摘　　要：提出基于先验知识和区域信息的参数活动轮廓模型(Snake 模型)图像分割.用包含先验知识和区域信息的变力替换在气球力 Snake 模型中的恒定气球力,并应用于模糊边界图像分割.实验结果表明,该模型与初始轮廓曲线位置无关,能完成自动分割模糊边界图像的任务.另外,对于均值相等、方差不同的目标和背景两区域图像实行分割,该模型也能获得正确的分割结果.Based on previous knowledge and region information , a novel parametric active contour model （Snake model） for image segmentation to ambiguous edge is described in this paper. In the proposed model , constant force in the balloon snake model is replaced by variable force which incorporates with previous knowledge and two regions information of foreground and background, Experiments prove that the proposed model is robust to initial contour places and it can segment ambiguous edge image automatically. In addition, result of segmentation to two regions that have identical mean and different variation is correct.

关 键 词：图像分割 SNAKE模型 模糊边界 轮廓曲线 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]