Abstract
This paper firstly made analysis of the points, lines and surfaces with special curvatures in point cloud data information and classified the points according to the three eigenvalues obtained through analysis matrix. And then, it simplified the point cloud data. Data simplification was completed according to distance, surface variation, and curvature. At last, it screened, removed and classified the data based on the least square method applied in the fuzzy clustering analysis in local domain, so as to fit the point cloud surface and improve the extraction precision of the entire data.
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