Crawl through Neighbors: A Simple Curve Reconstruction Algorithm

Given a planar point set sampled from an object boundary, the process of approximating the original shape is called curve reconstruction. In this paper, a novel non‐parametric curve reconstruction algorithm based on Delaunay triangulation has been proposed and it has been theoretically proved that t...

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Bibliographic Details
Published in:Computer graphics forum Vol. 35; no. 5; pp. 177 - 186
Main Authors: Parakkat, Amal Dev, Muthuganapathy, Ramanathan
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.08.2016
Subjects:
Algorithms
Analysis
Approximation
Boundaries
Categories and Subject Descriptors (according to ACM CCS)
Computer graphics
Corners
Delaunay triangulation
I.3.3 [Computer Graphics]: Picture/Image Generation-Line and curve generation
Image processing systems
Reconstruction
Sketches
Skips
Studies
Topological manifolds
ISSN:0167-7055, 1467-8659
Online Access:Get full text
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Summary:Given a planar point set sampled from an object boundary, the process of approximating the original shape is called curve reconstruction. In this paper, a novel non‐parametric curve reconstruction algorithm based on Delaunay triangulation has been proposed and it has been theoretically proved that the proposed method reconstructs the original curve under ε‐sampling. Starting from an initial Delaunay seed edge, the algorithm proceeds by finding an appropriate neighbouring point and adding an edge between them. Experimental results show that the proposed algorithm is capable of reconstructing curves with different features like sharp corners, outliers, multiple objects, objects with holes, etc. The proposed method also works for open curves. Based on a study by a few users, the paper also discusses an application of the proposed algorithm for reconstructing hand drawn skip stroke sketches, which will be useful in various sketch based interfaces.
Bibliography:ark:/67375/WNG-5BPZKDTS-X
ArticleID:CGF12974
istex:59C4446F706F9F8AD25952C2E12B1E2D7569DF60
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ObjectType-Feature-1
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ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12974