摘要
针对大部分骨架计算方法对轮廓噪声的极端敏感性问题,该文提出一种基于贝叶斯模型的骨架裁剪方法。该方法利用贝叶斯理论对骨架及其生长过程进行建模,进而通过对模型的迭代优化实现骨架候选分支的筛选裁剪。由于已有的重建误差率在分析骨架时不能很好地体现骨架简洁程度,故该文在骨架重建误差率的基础上综合考虑骨架简洁度,提出骨架有效率的概念来对骨架做客观定量分析。实验结果表明该文算法对轮廓噪声具有较好的鲁棒性,且裁剪出的骨架相比现有算法得到的骨架结构更加简单,对形状描述更加准确。
Considering the problem that most of the existing skeleton calculation methods exhibit extreme sensitivity to the shape noise, a Bayes based algorithm for the skeleton pruning is proposed. The algorithm models the skeleton and growth process with Bayesian statistics framework. Based on the model, an iterative optimization is performed to prune the candidate branches. Due to the fact that the existing reconstruction error can not evaluate the simplicity of skeletons well, a new concept called Effective Rate is proposed to make quantitative analysis on the pruned skeleton with taking the simplicity into consideration. The experiments show that the proposed algorithm is robust to the shape noise and acts better in simplifying the skeleton structure and representing shape accurately.
出处
《电子与信息学报》
EI
CSCD
北大核心
2015年第9期2069-2075,共7页
Journal of Electronics & Information Technology
基金
国家自然科学基金青年科学基金(61100113)
国家教育部留学归国基金教外司留[2012]940号
重庆市首批青年骨干教师项目(渝教人(2011)31号)
重庆市基础与前沿研究计划项目(cstc2013jcyj A40062)
重庆邮电大学学科引进人才基金(A2010-12)
重庆市研究生科研创新项目(CYS14142)资助课题
关键词
骨架
形状
裁剪
贝叶斯
几何处理
骨架有效率
Skeleton
Shape
Pruning
Bayes
Geometry processing
Effective rate of skeleton
