基于向量内积的骨架提取算法

骨架是形状表示的重要特征,传统的骨架算法往往不能直接用于物体识别,且连通性难以保证.用求向量内积的方法对骨架进行提取,通过距离变换得到连接图像各点与最近边沿点的向量,并利用内积计算求取两个相邻点向量的内积值;再根据内积值进行骨架种子点的选择,经两次骨架生长处理得到连通的骨架.实验证明本算法复杂度低,能很好保证骨架的连通性.

Skeleton Extraction Algorithm Based on Vector Inner-Product

The skeleton is an important feature in the representation of shapes.Traditional skeletonization algorithm can not be used for skeleton recognition directly,and the connectivity property of the skeleton is not guaranteed.A skeleton extraction algorithm is proposed based upon vector inner-product.The vectors connecting image points to the nearest border points are determined by distance transform,the innerproduct is calculated between vectors from neighboring points.The seeds of skeleton are selected by the value of inner-product.A well connected skeleton is determined by two steps of skeleton growth.The proposed algorithm is proved to be with low time complexity.The skeleton is produced to be well connected.