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基于贝叶斯模型的骨架裁剪方法

秦红星 孙颖

秦红星, 孙颖. 基于贝叶斯模型的骨架裁剪方法[J]. 电子与信息学报, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003
引用本文: 秦红星, 孙颖. 基于贝叶斯模型的骨架裁剪方法[J]. 电子与信息学报, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003
Qin Hong-xing, Sun Ying. Approach of Skeleton Pruning with Bayesian Model[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003
Citation: Qin Hong-xing, Sun Ying. Approach of Skeleton Pruning with Bayesian Model[J]. Journal of Electronics & Information Technology, 2015, 37(9): 2069-2075. doi: 10.11999/JEIT150003

基于贝叶斯模型的骨架裁剪方法

doi: 10.11999/JEIT150003
基金项目: 

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(cstc2013jcyjA40062),重庆邮电大学学科引进人才基金(A2010-12)和重庆市研究生科研创新项目(CYS14142)

Approach of Skeleton Pruning with Bayesian Model

  • 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。
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出版历程
  • 收稿日期:  2015-01-05
  • 修回日期:  2015-05-13
  • 刊出日期:  2015-09-19

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