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Optical Engineering

360-deg profile noncontact measurement using a neural network
Author(s): Ming Chang; Wen-Chih Tai
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Paper Abstract

A new approach to automatic 3-D shape measurement is presented and verified by experiments. This approach, based on neural network theory, can automatically and accurately obtain the profile of diffuse 3-D objects by using a projected laser stripe. When the laser stripe is projected on an object, the line image of the laser light is grasped by a CCD camera. Using neural network theory, a relationship between the laser stripe image in the CCD camera and the related absolute position in space can be established. Thus the spatial coordinates of a measured line image in a CCD camera can be obtained according to the output value of the neural network. By processing a series of laser line images from the discrete angular positions of an object, a complete 3-D profile can be reconstructed. Theoretical analysis and experimental systems are presented. Experimental results show that this approach can determine the 360-deg profile of an object with an accuracy of 0.4 mm.

Paper Details

Date Published: 1 December 1995
PDF: 5 pages
Opt. Eng. 34(12) doi: 10.1117/12.215483
Published in: Optical Engineering Volume 34, Issue 12
Show Author Affiliations
Ming Chang, Chung Yuan Christian Univ. (China)
Wen-Chih Tai, Chung Yuan Christian Univ. (China)

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