The NURBS book
Fitting smooth surfaces to dense polygon meshes
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Ordering and Parameterizing Scattered 3D Data for B-Spline Surface Approximation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Advanced surface fitting techniques
Computer Aided Geometric Design
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Automatic Knot Placement by a Genetic Algorithm for Data Fitting with a Spline
SMI '99 Proceedings of the International Conference on Shape Modeling and Applications
Capturing Outline of Fonts Using Genetic Algorithm and Splines
IV '01 Proceedings of the Fifth International Conference on Information Visualisation
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
A new approach to solve hybrid flow shop scheduling problems by artificial immune system
Future Generation Computer Systems - Special issue: Computational science of lattice Boltzmann modelling
Functional networks for B-spline surface reconstruction
Future Generation Computer Systems - Special issue: Computer graphics and geometric modeling
Spline curve approximation and design by optimal control over the knots
Computing - Geometric modelling dagstuhl 2002
Error-Bounded B-Spline Curve Approximation Based on Dominant Point Selection
CGIV '05 Proceedings of the International Conference on Computer Graphics, Imaging and Visualization
Adaptive knot placement in B-spline curve approximation
Computer-Aided Design
Computing optimized curves with NURBS using evolutionary intelligence
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and its Applications - Volume Part I
Developable surface modelling by neural network
Mathematical and Computer Modelling: An International Journal
Using simulated annealing for knot placement for cubic spline approximation
MMES'10 Proceedings of the 2010 international conference on Mathematical models for engineering science
Information Sciences: an International Journal
Efficient particle swarm optimization approach for data fitting with free knot B-splines
Computer-Aided Design
Information Sciences: an International Journal
Structural design of the danger model immune algorithm
Information Sciences: an International Journal
Latent nonuniform splines for animation approximation
SIGGRAPH Asia 2012 Technical Briefs
A new iterative mutually coupled hybrid GA-PSO approach for curve fitting in manufacturing
Applied Soft Computing
Hi-index | 0.07 |
Reverse engineering transforms real parts into engineering concepts or models. First, sampled points are mapped from the object's surface by using tools such as laser scanners or cameras. Then, the sampled points are fitted to a free-form surface or a standard shape by using one of the geometric modeling techniques. The curves on the surface have to be modeled before surface modeling. In order to obtain a good B-spline curve model from large data, the knots are usually respected as variables. A curve is then modeled as a continuous, nonlinear and multivariate optimization problem with many local optima. For this reason it is very difficult to reach a global optimum. In this paper, we convert the original problem into a discrete combinatorial optimization problem like in Yoshimoto et al. [F. Yoshimoto, M. Moriyama, T. Harada, Automatic knot placement by a genetic algorithm for data fitting with a spline, in: Proceedings of the International Conference on Shape Modeling and Applications, IEEE Computer Society Press, 1999, pp. 162-169] and Sarfraz et al. [M. Sarfraz, S.A. Raza, Capturing outline of fonts using genetic algorithm and splines, in: Fifth International Conference on Information Visualisation (IV'01), 2001, pp. 738-743]. Then, we suggest a new method that solves the converted problem by artificial immune systems. We think the candidates of the locations of knots as antibodies. We define the affinity measure benefit from Akaike's Information Criterion (AIC). The proposed method determines the appropriate location of knots automatically and simultaneously. Furthermore, we do not need any subjective parameter or good population of initial location of knots for a good iterative search. Some examples are also given to demonstrate the efficiency and effectiveness of our method.