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.
Skeleton describes the topological structure of objects,and it is located at the geometric center of objects,which is a simple representation of the original object.Image skeleton can be defined as the trajectory of the maximum inscribed circle center,which is recognized as the most accurate description method.Skeleton extraction method is mainly divided into two categories：one is based on the distance field,and the other is based on thinning.Skeleton extracted with distance field method is composed of discrete maximum points,which is not continuous.On the other side,the skeleton extracted with thinning algorithm is easy to deviate from the original center of the image,which is not in conformity with the definition of largest inscribed circle trajectory.Our work is based on the advantage of these two kinds of algorithm.The algorithm of K3M is the most excellent one in thinning field.This algorithm can get a skeleton with a pixel width,and the process of iterative is clear,whose result can maintain the same angle of intersecting line as the original image at junctions.So it is widely used to extract skeleton for various types of image.The K3M algorithm is essentially a iterative thinning algorithm.Because the image data is discrete,so the iterative process cannot be strictly in accordance with the image contraction direction,and the skeleton locating is not accurate enough.Distance transform is an effective method to indicate image center.For a binary image,define a distance value for each internal pixel of the object,which is the shortest distance of this pixel to the target edge,such that the distance values corresponding to all object pixels form a distance field.The calculation of chessboard distance is simple,and it can satisfy general applications,so it is usually used for distance transform.For improving the centralization property of skeleton for K3M algorithm,distance transformation is introduced,and the K3M skeleton extraction algorithm is proposed in this article.Implementing distance transformation on the object image,get the distance field;running the K3M algorithm on the contours of distance field,according to the order from little to large;as the last step,make the width of the skeleton is 1 pixel.Experiments of this algorithm with lots of different kinds of images have been finished,the skeleton extracted with which fit the spine of distance field more closely than K3M algorithm,and satisfy the skeleton definition of maximum incircle.The results of the experiments indicate that this algorithm will play an important role in both theoretical research and practical application.
出处
《南京大学学报（自然科学版）》
CAS
CSCD
北大核心
2013年第2期189-195,共7页
Journal of Nanjing University（Natural Science）
基金
国家自然科学基金(60970058)
江苏省自然科学基金(BK2009131)
苏州市科技基础设施建设计划(SZS201009)
苏州市职业大学创新团队建设项目(3100125)
苏州市职业大学校级课题(2012SZDYY04)
江苏省青蓝工程
关键词
二值图像
骨架
距离场
细化
Binary image
skeleton
distance field
thinning
