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Reconstruction of Curve Networks from Unorganized Spatial Points
Author(s) -
Shuangbu Wang,
Yu Xia,
Lihua You,
Jianjun Zhang
Publication year - 2020
Publication title -
jucs - journal of universal computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.284
H-Index - 53
eISSN - 0948-695X
pISSN - 0948-6968
DOI - 10.3897/jucs.2020.065
Subject(s) - computer science , curve fitting , data point , euclidean distance , euclidean geometry , algorithm , set (abstract data type) , artificial intelligence , mathematics , geometry , machine learning , programming language
Curve network reconstruction from a set of unorganized points is an important problem in reverse engineering and computer graphics. In this paper, we propose an automatic method to extract curve segments and reconstruct curve networks from unorganized spatial points. Our proposed method divides reconstruction of curve networks into two steps: 1) detecting nodes of curve segments and 2) reconstructing curve segments. For detection of nodes of curve segments, we present a principal component analysis-based algorithm to obtain candidate nodes from unorganized spatial points and a Euclidean distance-based iterative algorithm to remove peripheral nodes and find the actual nodes. For reconstruction of curve segments, we propose an extraction algorithm to obtain the points on each of curve segments. We present quite a number of examples which use our proposed method to reconstruct curve networks from unorganized spatial points. The results demonstrate the effectiveness of our proposed method and its advantages of good automation and high reconstruction efficiency.

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