Highly Anti-Noise and Adaptive B-Spline Curve Reconstruction Based on ICT Slice Images

Abstract:

Obtaining effective value points is one of key issues in cubic B-spline curve reconstruction. Since it is unfavorable for the selection of value points through curvature methods and the point cloud data acquired from ICT slice images is characterized with large volume of data, high noise and density, a baseline adaptive method is presented to get value points for curve reconstruction, baseline and scale threshold determined by wavelet multi-scale, in which the value points is obtained and curve is reconstructed automatically. Hausdorff distance is adopted to calculate the error of cubic B-spline curve reconstruction. Comparative analysis with existing methods proves that our method can effectively restrain noise and quickly reconstruct contour curves.

• Periodical: Applied Mechanics and Materials (Volumes 397-400)
• Pages: 1083-1087
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.397-400.1083
• Online since: September 2013
• Authors: Guang Shuai Liu, Bai Lin Li
• Keywords: Adaptive Baseline, Curve Reconstruction, Error Evaluation, Wavelet Multi-Scale

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