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Proceedings Paper

Iterative refining algorithm for regularization
Author(s): Francesco P. Lovergine; Ettore Stella; Arcangelo Distante
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Paper Abstract

The work here presented proposes an iterative refining algorithm to build a sequence of convex functionals based essentially on a weak thin-plate under tension model for smoothing. This algorithm is applied to structure estimation and edge detection problems. The sequence of functionals is obtained by modifying continuously and iteratively continuous non-binary line processes which control regularity of the surface. This is done by comparing the smoothed estimation with initial data (sparse or dense), that is evaluating signal-to-noise characteristics.

Paper Details

Date Published: 13 October 1994
PDF: 7 pages
Proc. SPIE 2354, Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision, (13 October 1994); doi: 10.1117/12.189100
Show Author Affiliations
Francesco P. Lovergine, Istituto Elaborazione Segnali ed Immagini/CNR (Italy)
Ettore Stella, Istituto Elaborazione Segnali ed Immagini/CNR (Italy)
Arcangelo Distante, Istituto Elaborazione Segnali ed Immagini/CNR (Italy)


Published in SPIE Proceedings Vol. 2354:
Intelligent Robots and Computer Vision XIII: 3D Vision, Product Inspection, and Active Vision
David P. Casasent, Editor(s)

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