Point Cloud Simplification Algorithm of Quadric Error Based on the Optimal Neighborhood

doi:10.13474/j.cnki.11-2246.2018.0392

Abstract

Abstract: Point cloud simplification algorithm of quadric error based on the optimal neighborhood is proposed,aiming at solving the problem of error accumulated and error transferred.The feature points are extracted based on the geometric properties of point cloud neighborhood.The entropy function is built based on dimension feature,the optimal neighborhood is determined with the minimum entropy function principle,the non-feature of point cloud simplification is realized with the theory of quadric surface fitting error control combined.The result of the simplified is evaluated by the information entropy function based on quadric error evaluation index.Experiment shows that the algorithm can effectively decrease error influence,better service in the late of surface reconstruction.

Key words: dimension feature, the optimal neighborhood, quadric error, point cloud simplification, the information entropy

CLC Number:

P234.4

LU Jianhua, LIU Chuang, LÜ Zhicai. Point Cloud Simplification Algorithm of Quadric Error Based on the Optimal Neighborhood[J]. 测绘通报, 2018, 0(12): 101-104,113.

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