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摘要: 常见骨架提取算法对复杂多变的目标边缘具有较强的敏感性, 提取出的骨架曲线结构相对复杂, 数据量仍然较大. 针对这一问题, 提出了一种新的骨架曲线多边形近似算法. 该算法结合骨架曲线的特点, 在传统串行多边形近似算法的基础上引入了平滑度保持、结构特征保持以及拓扑特征保持等约束条件, 既较好地保留了原始骨架的主要拓扑结构特征, 又有效地简化了骨架曲线的结构, 进一步压缩了数据. 仿真研究证明了该方法的有效性.Abstract: High sensitivity of most skeletonization algorithms to the variable edge features makes the structure of the extracted skeletons relatively complicated and the corresponding data excessive. To solve this problem, a novel skeleton polygonal approximation algorithm is proposed. Several impactful improvements such as smoothness-preservation, structure-preservation, and topo-preservation have been proposed to characterize the main structure of the original skeleton as well as predigest other trivial structure for compression of redundant information. The new algorithm is thus superior to the conventional one. Simulation tests have verified the effectiveness of the algorithm.
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Key words:
- Skeleton /
- polygonal approximation /
- shape analysis
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