A divide-and-conquer algorithm for curve fitting

Curve fitting is still an open problem which draws attention from many applications, such as computer-aided design, computer-aided manufacturing and reverse engineering. Splines such as Bézier, B-Spline and NURBS curves are usually employed in engineering applications and are intensively used for fi...

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Vydáno v:Computer aided design Ročník 151; s. 103362
Hlavní autoři: Buchinger, Diego, Rosso, Roberto Silvio Ubertino
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.10.2022
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ISSN:0010-4485, 1879-2685
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Abstract Curve fitting is still an open problem which draws attention from many applications, such as computer-aided design, computer-aided manufacturing and reverse engineering. Splines such as Bézier, B-Spline and NURBS curves are usually employed in engineering applications and are intensively used for fitting purposes. The optimization of their shapes and localization parameters, however, is a very complex task. The literature presents many methods which empirically set some important parameters, such as the number of control points. As guessing such a value is difficult, this paper presents a new method to choose it through a multi-curve fitting method, based on linear least square optimizations, using a divide-and-conquer algorithm and an error tolerance threshold. Four prime procedures compose the method: the conquer step fits curves over subset point clouds; the combine step glues curve segments together with some selective continuity; the divide step splits subsets which are not properly fitted yet; and the merge step blends curve segments together. Several curve setups were tested in well-known benchmarks, using four-division strategies: bisection, error balance, point with the greatest curvature and point with the smallest curvature. The developed method allows for fast computation even for larger point clouds, and it was able to properly reconstruct each tested shape, even with the addition of synthetic noise. We also demonstrate that it can be significantly faster than a single-curve fitting using the same number of control points. •A multiple curve fitting approach using iterative multi-control-point insertion.•A divide-and-conquer algorithm allows for fast curve fitting.•Point cloud division strategies have their own pros and cons in curve fitting.•Adequate error tolerance balances quality and simplicity in curve fitting.
AbstractList Curve fitting is still an open problem which draws attention from many applications, such as computer-aided design, computer-aided manufacturing and reverse engineering. Splines such as Bézier, B-Spline and NURBS curves are usually employed in engineering applications and are intensively used for fitting purposes. The optimization of their shapes and localization parameters, however, is a very complex task. The literature presents many methods which empirically set some important parameters, such as the number of control points. As guessing such a value is difficult, this paper presents a new method to choose it through a multi-curve fitting method, based on linear least square optimizations, using a divide-and-conquer algorithm and an error tolerance threshold. Four prime procedures compose the method: the conquer step fits curves over subset point clouds; the combine step glues curve segments together with some selective continuity; the divide step splits subsets which are not properly fitted yet; and the merge step blends curve segments together. Several curve setups were tested in well-known benchmarks, using four-division strategies: bisection, error balance, point with the greatest curvature and point with the smallest curvature. The developed method allows for fast computation even for larger point clouds, and it was able to properly reconstruct each tested shape, even with the addition of synthetic noise. We also demonstrate that it can be significantly faster than a single-curve fitting using the same number of control points. •A multiple curve fitting approach using iterative multi-control-point insertion.•A divide-and-conquer algorithm allows for fast curve fitting.•Point cloud division strategies have their own pros and cons in curve fitting.•Adequate error tolerance balances quality and simplicity in curve fitting.
ArticleNumber 103362
Author Rosso, Roberto Silvio Ubertino
Buchinger, Diego
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Cites_doi 10.1016/j.ins.2010.09.031
10.1111/cgf.12802
10.1090/noti1578
10.1016/j.cagd.2012.03.004
10.3182/20130522-3-BR-4036.00098
10.1007/s11042-018-6109-z
10.1007/BF01436075
10.1016/j.cad.2013.04.006
10.1016/0010-4485(93)90011-C
10.1016/j.cad.2006.12.006
10.1007/s00500-020-05114-0
10.1115/1.4040981
10.1109/34.31447
10.1016/j.cad.2012.02.011
10.1371/journal.pone.0173857
10.1007/s10957-017-1192-2
10.1007/s10710-014-9231-3
10.1016/S0167-8396(98)00024-7
10.1016/S0010-4485(03)00006-X
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Keywords Curve reconstruction
Data fitting
Divide-and-conquer algorithm
Bézier
B-splines
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References Crane, Wardetzky (b34) 2017; 64
Garcia-Capulin, Cuevas, Trejo-Caballero, Rostro-Gonzalez (b15) 2015; 16
Costa, Montemurro, Pailhès (b28) 2018; 176
Sarfraz, Hussain, Irshad (b4) 2013; 7
Golub (b24) 1965; 7
Berger, Tagliasacchi, Seversky, Alliez, Levine, Sharf, Silva (b18) 2014
Ebrahimi, Loghmani (b6) 2017
Yoshimoto, Harada, Yoshimoto (b9) 2003; 35
Ueda, Sato, Martins, Takimoto, Rosso Jr., Tsuzuki (b29) 2020; 24
Yoshimoto, Moriyama, Harada (b8) 1999
Mortenson (b12) 2006
Gálvez, Iglesias, Puig-Pey (b3) 2012; 182
Dung, Tjahjowidodo (b16) 2017; 12
Ebrahimi, Loghmani (b7) 2018; 77
Javidrad (b22) 2012; 12
Hasegawa, Tormena, Parpinelli (b10) 2014; 11
Zheng, Bo, Liu, Wang (b20) 2012; 29
Laurent-Gengoux, Mekhilef (b27) 1993; 25
Irshad, Khalid, Hussain, Sarfraz (b21) 2016; 274
Gálvez, Iglesias (b14) 2013
Piegl, Tiller (b11) 1997
Berger, Tagliasacchi, Seversky, Alliez, Guennebaud, Levine, Sharf, Silva (b17) 2017; 36
Aguilar, Elizalde, Cárdenas, Probst, Marzocca, Ramirez (b32) 2018; 18
Kineri, Wang, Lin, Maekawa (b36) 2012; 44
Afshar, Soryani, Rahmani (b2) 2011; vol. 7077
Speer, Kuppe, Hoschek (b23) 1998; 15
Hasegawa, Rosso, Jr., Tsuzuki (b30) 2013; 46
Pandunata, Shamsuddin (b1) 2010
Teh, Chin (b38) 1989; 11
Hermann, Klette (b33) 2007
Cormen, Leiserson, Rivest, Stein (b26) 2009
Gonzalez, Woods (b35) 2008
Carlson, Gulliksson (b13) 2008
Park, Lee (b19) 2007; 39
Gálvez, Iglesias (b5) 2016; 275
Golub, Van Loan (b25) 1996
Sarfraz, Sait, Balah, Baig (b31) 2006
Wang, Zheng (b37) 2013; 45
Gálvez (10.1016/j.cad.2022.103362_b3) 2012; 182
Javidrad (10.1016/j.cad.2022.103362_b22) 2012; 12
Ueda (10.1016/j.cad.2022.103362_b29) 2020; 24
Hasegawa (10.1016/j.cad.2022.103362_b30) 2013; 46
Hermann (10.1016/j.cad.2022.103362_b33) 2007
Carlson (10.1016/j.cad.2022.103362_b13) 2008
Golub (10.1016/j.cad.2022.103362_b24) 1965; 7
Hasegawa (10.1016/j.cad.2022.103362_b10) 2014; 11
Sarfraz (10.1016/j.cad.2022.103362_b31) 2006
Garcia-Capulin (10.1016/j.cad.2022.103362_b15) 2015; 16
Yoshimoto (10.1016/j.cad.2022.103362_b9) 2003; 35
Piegl (10.1016/j.cad.2022.103362_b11) 1997
Gonzalez (10.1016/j.cad.2022.103362_b35) 2008
Aguilar (10.1016/j.cad.2022.103362_b32) 2018; 18
Mortenson (10.1016/j.cad.2022.103362_b12) 2006
Berger (10.1016/j.cad.2022.103362_b17) 2017; 36
Gálvez (10.1016/j.cad.2022.103362_b5) 2016; 275
Gálvez (10.1016/j.cad.2022.103362_b14) 2013
Ebrahimi (10.1016/j.cad.2022.103362_b6) 2017
Sarfraz (10.1016/j.cad.2022.103362_b4) 2013; 7
Ebrahimi (10.1016/j.cad.2022.103362_b7) 2018; 77
Afshar (10.1016/j.cad.2022.103362_b2) 2011; vol. 7077
Pandunata (10.1016/j.cad.2022.103362_b1) 2010
Golub (10.1016/j.cad.2022.103362_b25) 1996
Park (10.1016/j.cad.2022.103362_b19) 2007; 39
Wang (10.1016/j.cad.2022.103362_b37) 2013; 45
Berger (10.1016/j.cad.2022.103362_b18) 2014
Dung (10.1016/j.cad.2022.103362_b16) 2017; 12
Speer (10.1016/j.cad.2022.103362_b23) 1998; 15
Laurent-Gengoux (10.1016/j.cad.2022.103362_b27) 1993; 25
Kineri (10.1016/j.cad.2022.103362_b36) 2012; 44
Costa (10.1016/j.cad.2022.103362_b28) 2018; 176
Teh (10.1016/j.cad.2022.103362_b38) 1989; 11
Cormen (10.1016/j.cad.2022.103362_b26) 2009
Crane (10.1016/j.cad.2022.103362_b34) 2017; 64
Zheng (10.1016/j.cad.2022.103362_b20) 2012; 29
Irshad (10.1016/j.cad.2022.103362_b21) 2016; 274
Yoshimoto (10.1016/j.cad.2022.103362_b8) 1999
References_xml – volume: 15
  start-page: 869
  year: 1998
  end-page: 877
  ident: b23
  article-title: Global reparametrization for curve approximation
  publication-title: Comput Aided Geom Design
– volume: 275
  start-page: 195
  year: 2016
  end-page: 212
  ident: b5
  article-title: Particle-based meta-model for continuous breakpoint optimization in smooth local-support curve fitting
  publication-title: Appl Math Comput
– volume: 176
  start-page: 225
  year: 2018
  end-page: 251
  ident: b28
  article-title: A general hybrid optimization strategy for curve fitting in the non-uniform rational basis spline framework
  publication-title: J Optim Theory Appl
– volume: 11
  start-page: 859
  year: 1989
  end-page: 872
  ident: b38
  article-title: On the detection of dominant points on digital curve
  publication-title: IEEE Trans Pattern Anal Mach Intell
– start-page: 8
  year: 1999
  ident: b8
  article-title: Automatic knot placement by a genetic algorithm for data fitting with a spline
  publication-title: International conference on shape modeling and applications
– start-page: 694
  year: 1996
  ident: b25
  article-title: Matrix computations
– volume: 77
  start-page: 30331
  year: 2018
  end-page: 30351
  ident: b7
  article-title: Shape modeling based on specifying the initial B-spline curve and scaled BFGS optimization method
  publication-title: Multimedia Tools Appl
– start-page: 505
  year: 2006
  ident: b12
  article-title: Geometric modeling
– volume: 64
  start-page: 1153
  year: 2017
  end-page: 1159
  ident: b34
  article-title: A glimpse into discrete differential geometry
  publication-title: Notices Amer Math Soc
– volume: 24
  start-page: 18821
  year: 2020
  end-page: 18839
  ident: b29
  article-title: Curve approximation by adaptive neighborhood simulated annealing and piecewise bézier curves
  publication-title: Soft Comput Vol
– volume: 11
  start-page: 18
  year: 2014
  ident: b10
  article-title: Bézier curve parametrization using a multiobjective evolutionary algorithm
  publication-title: Int J Comput Sci Appl
– volume: 35
  start-page: 751
  year: 2003
  end-page: 760
  ident: b9
  article-title: Data fitting with a spline using a real-coded genetic algorithm
  publication-title: Comput Aided Des
– year: 2009
  ident: b26
  article-title: Introduction to algorithms
– start-page: 584
  year: 2007
  end-page: 589
  ident: b33
  article-title: A comparative study on 2D curvature estimators
  publication-title: 2007 International conference on computing: theory and applications (ICCTA’07)
– volume: 46
  start-page: 233
  year: 2013
  end-page: 238
  ident: b30
  article-title: Bézier curve fitting with a parallel differential evolution algorithm
  publication-title: IFAC Proc Vol
– year: 2013
  ident: b14
  article-title: Firefly algorithm for explicit B-spline curve fitting to data points
  publication-title: Mathematical problems in engineering, vol. 2013
– start-page: 954
  year: 2008
  ident: b35
  article-title: Digital image processing
– volume: vol. 7077
  start-page: 201
  year: 2011
  end-page: 210
  ident: b2
  article-title: Curve fitting using coevolutionary genetic algorithms
  publication-title: Swarm, evolutionary, and memetic computing (SEMCCO 2011)
– start-page: 35
  year: 2006
  end-page: 44
  ident: b31
  article-title: Computing optimized NURBS curves using simulated evolution on control parameters
  publication-title: Applications of soft computing, vol. 36
– volume: 7
  start-page: 206
  year: 1965
  end-page: 216
  ident: b24
  article-title: Numerical methods for solving linear least squares problems
  publication-title: Numer Math
– volume: 18
  start-page: 9
  year: 2018
  ident: b32
  article-title: An adaptive curvature-guided approach for the knot-placement problem in fitted splines
  publication-title: J Comput Inf Sci Eng
– volume: 39
  start-page: 439
  year: 2007
  end-page: 451
  ident: b19
  article-title: B-spline curve fitting based on adaptive curve refinement using dominant points
  publication-title: Comput Aided Des
– volume: 274
  start-page: 661
  year: 2016
  end-page: 678
  ident: b21
  article-title: Outline capturing using rational functions with the help of genetic algorithm
  publication-title: Appl Math Comput
– volume: 7
  start-page: 10
  year: 2013
  ident: b4
  article-title: Reverse engineering of the digital curve outlines using genetic algorithm
  publication-title: Int J Comput
– start-page: 25
  year: 2014
  ident: b18
  article-title: State of the art in surface reconstruction from point clouds
  publication-title: Eurographics 2014 - state of the art reports
– start-page: 169
  year: 2008
  end-page: 174
  ident: b13
  article-title: Surface fitting with NURBS: A Gauss Newton with trust region approach
  publication-title: 13th WSEAS international conference on applied mathematics
– volume: 182
  start-page: 56
  year: 2012
  end-page: 76
  ident: b3
  article-title: Iterative two-step genetic-algorithm-based method for efficient polynomial B-spline surface reconstruction
  publication-title: Inform Sci
– volume: 16
  start-page: 151
  year: 2015
  end-page: 166
  ident: b15
  article-title: A hierarchical genetic algorithm approach for curve fitting with B-splines
  publication-title: Genetic Program Evol Mach
– volume: 45
  start-page: 1095
  year: 2013
  end-page: 1107
  ident: b37
  article-title: Curvature-guided adaptive t-spline surface fitting
  publication-title: Comput Aided Des
– volume: 25
  start-page: 699
  year: 1993
  end-page: 710
  ident: b27
  article-title: Optimization of a NURBS representation
  publication-title: Comput Aided Des
– start-page: 12
  year: 2017
  ident: b6
  article-title: B-spline curve fitting by diagonal approximation BFGS methods
  publication-title: Iran J Sci Technol Trans A Sci
– start-page: 646
  year: 1997
  ident: b11
  article-title: The NURBS book
– volume: 44
  start-page: 697
  year: 2012
  end-page: 708
  ident: b36
  article-title: B-spline surface fitting by iterative geometric interpolation/approximation algorithms
  publication-title: Comput Aided Des
– volume: 12
  start-page: 24
  year: 2017
  ident: b16
  article-title: A direct method to solve optimal knots of B-spline curves: An application for non-uniform B-spline curves fitting
  publication-title: PLoS One
– volume: 12
  start-page: 11
  year: 2012
  ident: b22
  article-title: An accelerated simulated annealing method for B-spline curve fitting to strip shaped scattered points
  publication-title: Int J CAD/CAM (IJCC)
– volume: 36
  start-page: 301
  year: 2017
  end-page: 329
  ident: b17
  article-title: A survey of surface reconstruction from point clouds
  publication-title: Comput Graph Forum
– volume: 29
  start-page: 448
  year: 2012
  end-page: 462
  ident: b20
  article-title: Fast B-spline curve fitting by L-BFGS
  publication-title: Comput Aided Geom Design
– start-page: 68
  year: 2010
  end-page: 72
  ident: b1
  article-title: Differential evolution optimization for bezier curve fitting
  publication-title: Seventh international conference on computer graphics, imaging and visualization
– year: 2013
  ident: 10.1016/j.cad.2022.103362_b14
  article-title: Firefly algorithm for explicit B-spline curve fitting to data points
– volume: 182
  start-page: 56
  issue: 1
  year: 2012
  ident: 10.1016/j.cad.2022.103362_b3
  article-title: Iterative two-step genetic-algorithm-based method for efficient polynomial B-spline surface reconstruction
  publication-title: Inform Sci
  doi: 10.1016/j.ins.2010.09.031
– volume: 12
  start-page: 11
  issue: 1
  year: 2012
  ident: 10.1016/j.cad.2022.103362_b22
  article-title: An accelerated simulated annealing method for B-spline curve fitting to strip shaped scattered points
  publication-title: Int J CAD/CAM (IJCC)
– start-page: 954
  year: 2008
  ident: 10.1016/j.cad.2022.103362_b35
– volume: 36
  start-page: 301
  issue: 1
  year: 2017
  ident: 10.1016/j.cad.2022.103362_b17
  article-title: A survey of surface reconstruction from point clouds
  publication-title: Comput Graph Forum
  doi: 10.1111/cgf.12802
– volume: 64
  start-page: 1153
  year: 2017
  ident: 10.1016/j.cad.2022.103362_b34
  article-title: A glimpse into discrete differential geometry
  publication-title: Notices Amer Math Soc
  doi: 10.1090/noti1578
– volume: 29
  start-page: 448
  issue: 7
  year: 2012
  ident: 10.1016/j.cad.2022.103362_b20
  article-title: Fast B-spline curve fitting by L-BFGS
  publication-title: Comput Aided Geom Design
  doi: 10.1016/j.cagd.2012.03.004
– volume: 46
  start-page: 233
  issue: 7
  year: 2013
  ident: 10.1016/j.cad.2022.103362_b30
  article-title: Bézier curve fitting with a parallel differential evolution algorithm
  publication-title: IFAC Proc Vol
  doi: 10.3182/20130522-3-BR-4036.00098
– volume: 7
  start-page: 10
  year: 2013
  ident: 10.1016/j.cad.2022.103362_b4
  article-title: Reverse engineering of the digital curve outlines using genetic algorithm
  publication-title: Int J Comput
– volume: 77
  start-page: 30331
  issue: 23
  year: 2018
  ident: 10.1016/j.cad.2022.103362_b7
  article-title: Shape modeling based on specifying the initial B-spline curve and scaled BFGS optimization method
  publication-title: Multimedia Tools Appl
  doi: 10.1007/s11042-018-6109-z
– start-page: 8
  year: 1999
  ident: 10.1016/j.cad.2022.103362_b8
  article-title: Automatic knot placement by a genetic algorithm for data fitting with a spline
– start-page: 68
  year: 2010
  ident: 10.1016/j.cad.2022.103362_b1
  article-title: Differential evolution optimization for bezier curve fitting
– start-page: 505
  year: 2006
  ident: 10.1016/j.cad.2022.103362_b12
– volume: 7
  start-page: 206
  issue: 3
  year: 1965
  ident: 10.1016/j.cad.2022.103362_b24
  article-title: Numerical methods for solving linear least squares problems
  publication-title: Numer Math
  doi: 10.1007/BF01436075
– volume: 45
  start-page: 1095
  issue: 8–9
  year: 2013
  ident: 10.1016/j.cad.2022.103362_b37
  article-title: Curvature-guided adaptive t-spline surface fitting
  publication-title: Comput Aided Des
  doi: 10.1016/j.cad.2013.04.006
– volume: 275
  start-page: 195
  issue: 15
  year: 2016
  ident: 10.1016/j.cad.2022.103362_b5
  article-title: Particle-based meta-model for continuous breakpoint optimization in smooth local-support curve fitting
  publication-title: Appl Math Comput
– start-page: 584
  year: 2007
  ident: 10.1016/j.cad.2022.103362_b33
  article-title: A comparative study on 2D curvature estimators
– volume: 25
  start-page: 699
  issue: 11
  year: 1993
  ident: 10.1016/j.cad.2022.103362_b27
  article-title: Optimization of a NURBS representation
  publication-title: Comput Aided Des
  doi: 10.1016/0010-4485(93)90011-C
– start-page: 25
  year: 2014
  ident: 10.1016/j.cad.2022.103362_b18
  article-title: State of the art in surface reconstruction from point clouds
– volume: 39
  start-page: 439
  issue: 6
  year: 2007
  ident: 10.1016/j.cad.2022.103362_b19
  article-title: B-spline curve fitting based on adaptive curve refinement using dominant points
  publication-title: Comput Aided Des
  doi: 10.1016/j.cad.2006.12.006
– volume: vol. 7077
  start-page: 201
  year: 2011
  ident: 10.1016/j.cad.2022.103362_b2
  article-title: Curve fitting using coevolutionary genetic algorithms
– start-page: 12
  year: 2017
  ident: 10.1016/j.cad.2022.103362_b6
  article-title: B-spline curve fitting by diagonal approximation BFGS methods
  publication-title: Iran J Sci Technol Trans A Sci
– volume: 24
  start-page: 18821
  year: 2020
  ident: 10.1016/j.cad.2022.103362_b29
  article-title: Curve approximation by adaptive neighborhood simulated annealing and piecewise bézier curves
  publication-title: Soft Comput Vol
  doi: 10.1007/s00500-020-05114-0
– volume: 18
  start-page: 9
  issue: 4, Paper No: JCISE-15-1390
  year: 2018
  ident: 10.1016/j.cad.2022.103362_b32
  article-title: An adaptive curvature-guided approach for the knot-placement problem in fitted splines
  publication-title: J Comput Inf Sci Eng
  doi: 10.1115/1.4040981
– volume: 11
  start-page: 18
  issue: 2
  year: 2014
  ident: 10.1016/j.cad.2022.103362_b10
  article-title: Bézier curve parametrization using a multiobjective evolutionary algorithm
  publication-title: Int J Comput Sci Appl
– year: 2009
  ident: 10.1016/j.cad.2022.103362_b26
– volume: 11
  start-page: 859
  issue: 8
  year: 1989
  ident: 10.1016/j.cad.2022.103362_b38
  article-title: On the detection of dominant points on digital curve
  publication-title: IEEE Trans Pattern Anal Mach Intell
  doi: 10.1109/34.31447
– volume: 44
  start-page: 697
  issue: 7
  year: 2012
  ident: 10.1016/j.cad.2022.103362_b36
  article-title: B-spline surface fitting by iterative geometric interpolation/approximation algorithms
  publication-title: Comput Aided Des
  doi: 10.1016/j.cad.2012.02.011
– volume: 12
  start-page: 24
  issue: 3
  year: 2017
  ident: 10.1016/j.cad.2022.103362_b16
  article-title: A direct method to solve optimal knots of B-spline curves: An application for non-uniform B-spline curves fitting
  publication-title: PLoS One
  doi: 10.1371/journal.pone.0173857
– start-page: 35
  year: 2006
  ident: 10.1016/j.cad.2022.103362_b31
  article-title: Computing optimized NURBS curves using simulated evolution on control parameters
– volume: 176
  start-page: 225
  issue: 1
  year: 2018
  ident: 10.1016/j.cad.2022.103362_b28
  article-title: A general hybrid optimization strategy for curve fitting in the non-uniform rational basis spline framework
  publication-title: J Optim Theory Appl
  doi: 10.1007/s10957-017-1192-2
– volume: 16
  start-page: 151
  year: 2015
  ident: 10.1016/j.cad.2022.103362_b15
  article-title: A hierarchical genetic algorithm approach for curve fitting with B-splines
  publication-title: Genetic Program Evol Mach
  doi: 10.1007/s10710-014-9231-3
– volume: 274
  start-page: 661
  issue: 1
  year: 2016
  ident: 10.1016/j.cad.2022.103362_b21
  article-title: Outline capturing using rational functions with the help of genetic algorithm
  publication-title: Appl Math Comput
– start-page: 646
  year: 1997
  ident: 10.1016/j.cad.2022.103362_b11
– volume: 15
  start-page: 869
  issue: 9
  year: 1998
  ident: 10.1016/j.cad.2022.103362_b23
  article-title: Global reparametrization for curve approximation
  publication-title: Comput Aided Geom Design
  doi: 10.1016/S0167-8396(98)00024-7
– volume: 35
  start-page: 751
  issue: 8
  year: 2003
  ident: 10.1016/j.cad.2022.103362_b9
  article-title: Data fitting with a spline using a real-coded genetic algorithm
  publication-title: Comput Aided Des
  doi: 10.1016/S0010-4485(03)00006-X
– start-page: 694
  year: 1996
  ident: 10.1016/j.cad.2022.103362_b25
– start-page: 169
  year: 2008
  ident: 10.1016/j.cad.2022.103362_b13
  article-title: Surface fitting with NURBS: A Gauss Newton with trust region approach
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Snippet Curve fitting is still an open problem which draws attention from many applications, such as computer-aided design, computer-aided manufacturing and reverse...
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StartPage 103362
SubjectTerms B-splines
Bézier
Curve reconstruction
Data fitting
Divide-and-conquer algorithm
Title A divide-and-conquer algorithm for curve fitting
URI https://dx.doi.org/10.1016/j.cad.2022.103362
Volume 151
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