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An Effective Principal Curves Extraction Algorithm for Complex Distribution Dataset

机译:复杂分布数据集的有效主曲线提取算法

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摘要

This paper proposes a new method for finding principal curves from complex distribution dataset. Motivated by solving the problem, which is that existing methods did not perform well on finding principal curve in complex distribution dataset with high curvature, high dispersion and self-intersecting, such as spiral-shaped curves, Firstly, rudimentary principal graph of data set is created based on the thinning algorithm, and then the contiguous vertices are merged. Finally the fitting-and-smoothing step introduced by Kegl is improved to optimize the principal graph, and Kegl's restructuring step is used to rectify imperfections of principal graph. Experimental results indicate the effectiveness of the proposed method on finding principal curves in complex distribution dataset.
机译:本文提出了一种从复杂分布数据集中寻找主曲线的新方法。解决该问题的动机是,现有方法在高曲率,高分散和自相交的复杂分布数据集中找到主曲线(例如螺旋形曲线)效果不佳,首先是数据集的基本主图。基于细化算法创建的顶点,然后合并相邻的顶点。最后,改进了Kegl引入的拟合和平滑步骤以优化主图,并使用Kegl的重构步骤来纠正主图的缺陷。实验结果表明了该方法在复杂分布数据集中寻找主曲线的有效性。

著录项

  • 来源
    《Rough sets and knowledge technology》|2010年|p.328-335|共8页
  • 会议地点 Beijing(CN);Beijing(CN)
  • 作者单位

    The Key Laboratory of Embedded System and Service Computing, Ministry of Education, China, Tongji University, Shanghai 201804, China School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China;

    The Key Laboratory of Embedded System and Service Computing, Ministry of Education, China, Tongji University, Shanghai 201804, China School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China;

    The Key Laboratory of Embedded System and Service Computing, Ministry of Education, China, Tongji University, Shanghai 201804, China School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China;

    The Key Laboratory of Embedded System and Service Computing, Ministry of Education, China, Tongji University, Shanghai 201804, China School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 程序设计、软件工程;
  • 关键词

    principal curves; complex distribution dataset; thinning algorithm; fitting-smoothing step; image skeletonization;

    机译:主曲线复杂分布数据集;细化算法;平滑步骤图像骨架化;

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