Paper Title:
Profiles Detection in Ring Convex Forming by ACLN with Sub-Pixel Accuracy
  Abstract

An optical measuring system for the ring test is proposed. In this approach, the machine vision inspection equipment is first built to record and capture the images of ring test from the digital camcorder.The image processing procedures to detect and locate the edge points of the inner and outer radii in ring convex forming are presented. Unlike the conventional sub-pixel estimation based on gray-level values, the quantity (8 bits) of color’s scale has been adopted. In image processing procedures, a clustering method called Adaptive Competitive Learning Network (ACLN) is first used to classify the image hues which represent the different heights of bulge profiles on the top of ring, and then the edge points can be searched by the interpolation step of subpixel accuracy. The calibration curves constructed by the mode of non-constant friction factor called F-value approach is designed to compare and check with the measurement data. The experimental results will be presented and discussed in this study.

  Info
Periodical
Key Engineering Materials (Volumes 364-366)
Edited by
Guo Fan JIN, Wing Bun LEE, Chi Fai CHEUNG and Suet TO
Pages
199-204
DOI
10.4028/www.scientific.net/KEM.364-366.199
Citation
J. P. Wang, G. M. Huang, S. H. Yurs, "Profiles Detection in Ring Convex Forming by ACLN with Sub-Pixel Accuracy", Key Engineering Materials, Vols. 364-366, pp. 199-204, 2008
Online since
December 2007
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Price
$32.00
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