关键词: 局部离群点, k-近邻, 模型边界, 去噪

Abstract: Concerning the point clouds with noises and outliers acquired by a 3D scanner, a denoising method based on the concept of local outlier was proposed. The method established the topology connection of the scattered points by searching the k-Nearest Neighbor (kNN) of each point. Local outlier factor was calculated to weight the current point's outlier level, so the noises can be restricted and the outliers can be removed. The method emphasized how to detect the outliers and noises with low density when they are scattered around the point cloud with high density. The experimental results show that the method can detect the outliers next to model boundaries easily, and maintain the borders to the greatest extent.

Key words: local outlier, k-Nearest Neighbor (kNN), model boundary, denoising