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Proceedings Paper

Shape detection by applying a laser line and neural networks
Author(s): J. Apolinar Muñoz-Rodríguez
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Paper Abstract

A technique for shape detection using a laser line and neural networks is presented. In this technique, an object is scanned by means of a laser line. From the scanning, a set of images is captured by a CCD camera. By processing these images, the object shape is recovered. The topographic information is extracted from an image by detecting the laser line position in the image plane. To determine the mathematical model of the relationship between the laser line position and the object surface, neural networks are applied. To carry it out, Bezier functions are used to construct the architecture of the neural networks. Using neural networks in this technique, the object shape is obtained by image processing and the parameters of the optical set-up are avoided. In this manner, the accuracy of the topographic measurements is improved. The results of this examination are presented by computer simulation and experimentally verified.

Paper Details

Date Published: 10 February 2006
PDF: 7 pages
Proc. SPIE 6046, Fifth Symposium Optics in Industry, 60461L (10 February 2006); doi: 10.1117/12.674558
Show Author Affiliations
J. Apolinar Muñoz-Rodríguez, Ctr. de Investigaciones en Óptica, A. C. (Mexico)


Published in SPIE Proceedings Vol. 6046:
Fifth Symposium Optics in Industry
Eric Rosas; Rocío Cardoso; Juan C. Bermudez; Oracio Barbosa-García, Editor(s)

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