基于曲率弦高法的海量测量数据精简

doi:10.3969/j.issn.1000-1158.2015.03.02

Abstract
Figure/Table
References (0)
Related Citation (15)

Download: PDF (5036 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract In the field of vision measurement, the size of clouds data of the point which obtained in vision measurement process is so large that it is inconvenient to be calculated, stored and reconstructed. Based on the analysis of cloud data characteristics of vision measurement point, combined curvature principle with the chord height algorithm, a mass cloud data reducing method based on curvature chord height algorithm is presented. With this method, the function of the chord height was built considering the curvature variation of the curves, and the value of changing chord height of each point is obtained by iteration, and then the measurement points to be retained were determined based on the data reducing method of chord height algorithm. Simulation results showed that the cloud data reduced 89.8% through this method when the average error was less than 0.2mm.So the cloud data of mass points were reduced directly and effectively, and the reasonable distribution of measurement point according to the curvature of the surface was realized.

Key words： Metrology Vision measurement Curvature Chord height Data reduction

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	WU Feng-he
	WANG Xin
	SUN Ying-bing
	WANG Jun

Cite this article:

WU Feng-he,WANG Xin,SUN Ying-bing, et al. Massive Cloud Data Simplification Based onCurvature Hypotenuse-height Method[J]. Acta Metrologica Sinica, 2015, 36(3): 229-233.

URL:

http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2015.03.02 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2015/V36/I3/229