【摘要】 为了提高骨架提取的准确性和连通性,提出了一种基于向量内积的新型骨架提取方法。对二值图像进行欧氏距离变换,获得了由内部像素点指向边界点的边界向量,通过比较内部像素点8-邻域范围内对应边界向量内积值符号在4个方向上的变化情况确定了边界向量方向发生重大变化的次数,并据此选取候选骨架点;采用基于回归分析的方法确定延伸方向,并完成连接操作生成完整的骨架线。实验结果表明,该算法能够保证骨架的连通性和完整性,且骨架定位准确,平均正确率达到92.27%,同时可以克服边界扰动,是一种有效的骨架提取算法。更多还原

【Abstract】 A new method for skeleton extraction based on vector inner product was presented in order to improve the accuracy and connectivity.Euclidean distance transform is used to determine the nearest edge element for each pixel in a binary image.A vector from each pixel that stops at the nearest edge element is defined as edge vector.By comparing the inner product of edge vector within 8-neighborhood of the pixel,the number of significant changes in direction can be determined,and the candidate skeleton points can be selected according to it.Finally,a complete skeleton was generated by extending process based on regression analysis.Experimental results show that the algorithm can guarantee connectivity and integrity of the skeleton,and the average accuracy rate of location reached 92.27%.It also has advantages in reflecting the topological structures of objects and overcoming boundary disturbance.So,it is an effective skeleton extraction algorithm.更多还原