| 密度聚类算法在连续分布点云去噪中的应用 |
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| 引用本文： | 张巧英,陈浩,朱爽.密度聚类算法在连续分布点云去噪中的应用[J].地理空间信息,2011(6):101-104. |
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| 作者姓名： | 张巧英 陈浩 朱爽 |
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| 作者单位： | 浙江省测绘大队,浙江杭州,310007 |
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| 摘 要： | 在原始测量获取的点云数据中,除了目标数据外,还有大量的噪声数据。噪声往往无规律地分布在目标物体周围,难以用统一数学模型区分。基于密度的聚类算法将簇定义为密度相连的点的最大集合,能发现任意形状、大小的类簇,将该算法应用在点云去噪中,能将密度分布连续点进行聚类,从中提取出目标点云。
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| 关 键 词： | 基于密度的聚类 点云密度分布 点云去噪 |
Application of Density-based Clustering Algorithms in Noise Removing of Continuous Distributed Point Clouds |
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| Institution: | ZHANG Qiaoying |
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| Abstract: | There are lots of noise data in the raw data except the target data. And the noise data always distribute around the target object irregularly, it is impossible to build a math model to make a distinction between the noise data and target data. The cluster is defined as the maximum set of density-collected in Density-based clustering algorithms, it can discover arbitrary shaped or sized cluster. To apply this algorithm it the noise removing of point clouds, can make the continuous distributed points as a cluster, and then extract the target point clouds. |
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| Keywords: | Density-based clustering algorithms the density distribution of point cloud noise remove |
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