Abstract
This chapter deals with the problem of fitting curves to data points, a classical optimization problem in Computer-Aided Geometric Design (CAGD). This issue plays an important role in real problems such as construction of car bodies, ship hulls, airplane fuselage, and other free-form objects. A typical example comes from reverse engineering where free-form shapes are extracted from clouds of scanned data points. In this chapter we address this issue by applying a powerful bio-inspired method called Artificial Immune Systems (AIS). The AIS can be understood as a computational methodology based upon metaphors of the biological immune system. As such, there is not one but several AIS algorithms. In this chapter we focus on the clonal selection algorithm (CSA), which explicitly takes into account the affinity maturation of the immune response. This algorithm is applied to fit Bézier curves to given sets of data points. Some illustrative examples show the good performance of our approach.
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Iglesias, A., Gálvez, A., Avila, A. (2013). Discrete Bézier Curve Fitting with Artificial Immune Systems. In: Plemenos, D., Miaoulis, G. (eds) Intelligent Computer Graphics 2012. Studies in Computational Intelligence, vol 441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31745-3_4
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