Point Cloud Segmentation De-noising Method Based on Curvature Constraint
ZHANG Yu-cun1,LI Ya-bin1,FU Xian-bin2
1. Institute of Electrical Engineer, Yanshan University, Qinhuangdao, Hebei 066004, China
2. Institute of Information Engineer, Hebei University of Environmental Engineering, Qinhuangdao, Hebei 066102, China
Abstract：In the process of point cloud de-noising, point cloud segmentation de-noising method based on curvature constraint was proposed in order to improve the de-noising effect of the region with larger curvature change. In the mentioned method, curvature constrained point cloud data was used to keep the model features effectively, and noise smoothing mapping function was constructed to make the noise points regress smoothly, which could avoid over-smoothing the point cloud data model by traditional filtering and lay a foundation for subsequent processing. Experiments showed that the above method could effectively preserve the characteristics of the model, retain the edge information of the model, and the de-noising effect was more obvious than bilateral filtering.
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2020, Vol. 41 
