DocumentCode :
2702818
Title :
A cloud-point smoothing method based on surface feature
Author :
Zhang, Lianwei ; Zhong, Huijuan ; Liu, Xiaolin ; Chen, Wei ; He, Hangen
Author_Institution :
Coll. of Mechatron. Eng. & Autom., Nat. Univ. of Defence Technol., Changsha
fYear :
2008
fDate :
20-23 June 2008
Firstpage :
1677
Lastpage :
1680
Abstract :
A scattered cloud-point smoothing method based on surface feature is put forth by analyzing the surface local feature. The feature curvature proposed in this paper is a more accuracy parameter to present the contour of a surface. The method consists of three steps. Firstly, the normal of a point is estimated using covariance analysis. Secondly, the local surface is fitted through quadratic surface, by which the principal curvature and feature curvature are estimated. Lastly, the cloud-point data is smoothed using an anisotropic smoothing equation based on feature curvature. This method preserves model feature while decreasing noise. The efficiency of the proposed algorithm is proved by experiments.
Keywords :
covariance analysis; smoothing methods; solid modelling; surface fitting; 3D model; anisotropic smoothing equation; cloud-point smoothing method; covariance analysis; feature curvature; principal curvature; quadratic surface; surface contour; surface feature; surface fitting; Anisotropic magnetoresistance; Automation; Equations; Geometry; Image reconstruction; Light scattering; Smoothing methods; Solid modeling; Surface reconstruction; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation, 2008. ICIA 2008. International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-2183-1
Electronic_ISBN :
978-1-4244-2184-8
Type :
conf
DOI :
10.1109/ICINFA.2008.4608274
Filename :
4608274
Link To Document :
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