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Near outlier detection of scattered point cloud
ZHAO Jingdong, YANG Fenghua, LIU Aijng
Journal of Computer Applications    2015, 35 (4): 1089-1092.   DOI: 10.11772/j.issn.1001-9081.2015.04.1089
Abstract678)      PDF (747KB)(608)       Save

Concerning that the original Surface Variation based Local Outlier Factor (SVLOF) cannot filter out the outliers on edges or corners of three-dimensional solid, a new near outlier detection algorithm of scattered point cloud was proposed. This algorithm firstly defined SVLOF on the k neighborhood-like region, and expanded the definition of SVLOF. The expanded SVLOF can not only filter outliers on smooth surface but also filter outliers on edges or corners of three-dimensional solid. At the same time, it still retains the space of threshold value enough of original SVLOF. The experimental results of the simulation data and measured data show that the new algorithm can detect the near outliers of scattered point cloud effectively without changing the efficiency obviously.

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