RT Journal Article
T1 Robust fitting of Zernike polynomials to noisy point clouds defined over connected domains of arbitrary shape
A1 Rodríguez Ibáñez, Diego
A1 Gómez Pedrero, José Antonio
A1 Alonso Fernández, José
A1 Quiroga Mellado, Juan Antonio
AB A new method for fitting a series of Zernike polynomials to point clouds defined over connected domains of arbitrary shape defined within the unit circle is presented in this work. The method is based on the application of machine learning fitting techniques by constructing an extended training set in order to ensure the smooth variation of local curvature over the whole domain. Therefore this technique is best suited for fitting points corresponding to ophthalmic lenses surfaces, particularly progressive power ones, in non-regular domains. We have tested our method by fitting numerical and real surfaces reaching an accuracy of 1 micron in elevation and 0.1 D in local curvature in agreement with the customary tolerances in the ophthalmic manufacturing industry.
PB The Optical Society Of America
SN 1094-4087
YR 2016
FD 2016-03-21
LK https://hdl.handle.net/20.500.14352/24496
UL https://hdl.handle.net/20.500.14352/24496
LA eng
NO En abierto en la web del editor.Received 7 Oct 2015; revised 4 Feb 2016; accepted 9 Feb 2016; published 9 Mar 2016© 2016 Optical Society of America. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modifications of the content of this paper are prohibited.
NO Ministerio de Economía y Competitividad (MINECO)
DS Docta Complutense
RD 6 abr 2025