A B-Spline Curve Fitting Algorithm Based on Contour Key Points

HAN Jiang; JIANG Ben-chi; XIA Lian; LI Da-zhu

doi:10.3879/j.issn.1000-0887.2015.04.010

Volume 36 Issue 4

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HAN Jiang, JIANG Ben-chi, XIA Lian, LI Da-zhu. A B-Spline Curve Fitting Algorithm Based on Contour Key Points[J]. Applied Mathematics and Mechanics, 2015, 36(4): 423-431. doi: 10.3879/j.issn.1000-0887.2015.04.010

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A B-Spline Curve Fitting Algorithm Based on Contour Key Points

doi: 10.3879/j.issn.1000-0887.2015.04.010

Institute of CIMS, Hefei University of Technology, Hefei 230009, P.R.China

Funds: The National Natural Science Foundation of China（51275147）

Received Date: 2014-09-11
Rev Recd Date: 2015-01-12
Publish Date: 2015-04-15

Abstract

Abstract

Aimed at the sliced contour data points of point cloud in the reverse engineering, a B-spline curve fitting method based on contour key points was presented. Under the premise of keeping the shape fidelity, first, the scanned strip point set was resampled with an equidistance method and the contour key points were selected, in turn an initial interpolation curve was built. Next, the curve deviation values were calculated with a neighborhood point comparison method, and a new key point was added where the curve deviation value exceeded the specified tolerance, then a new interpolation curve was gained. The above procedure was repeated until the fitting curve reached expected accuracy. The numerical experiments show that, for the B-spline fitting of dense sectional scanned points, the proposed algorithm effectively compresses the number of key points and bears high computational efficiency. At the same time, since the distribution of key points accurately reflects the fitting curve’s curvature changes, this method also makes one promising iteration step in the curve approximation under deviation constraints.
- contour key point,
- B-spline,
- curve fitting,
- deviation constraint

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References(16)

References

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