南京大学学报(自然科学版) ›› 2013, Vol. 49 ›› Issue (2): 189195.
颜廷秦1·2**,周昌雄1,刘淑芬1
Yan Ting一Qin1.2,Zhou Chang一Xiong1,Liu Shu一Fen1
摘要: 骨架提取方法可分为两类:一是基于距离场的方法,其次是细化算法.距离场方法提取的骨架
由离散的极值点组成,能够准确定位图像中心,但是骨架是不连续的;细化算法提取的骨架连续性好,但
是容易偏离图像的中心.K3M算法是一种优秀的细化算法,能够提取不同类型图像的骨架,为了提高这
一算法提取骨架的居中性质,引入距离场概念,提出距离场约束的K3M骨架提取算法.对目标图像进行
距离转换,形成距离场;依据距离场的等高线,按从小到大的顺序依次进行K3M算法细化;最后,把骨架
处理为1个像素宽度.通过不同类型图像的大量实验,可以看出,这种方法提取的骨架与距离场脊线的
吻合度高,更加符合最大内切圆的骨架定义,具有一定的理论研究意义;同时算法能够很好地完成多种
类型图像的骨架提取,实用价值上也具有普遍意义.
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