Paper Title:
Quality Testing for Pressed Raised Character on Metal Label Using GRBF Networks
  Abstract

In accordance with the obvious characteristics of the pressed raised character image and the shortages of the template matching method.a new method of using the general radial-basis function neural network (GRBFN) for testing the quality of the pressed character is presented. The structures and training methods of GRBFN are fully analyzed, as well as the functionality of hidden layer, excited focus and area. The results show the checker based on GRBFN has highly checking ratio for the label pressed raised characters. It is suited to the quality testing of raised characters.

  Info
Periodical
Key Engineering Materials (Volumes 315-316)
Edited by
Zhejun Yuan, Xipeng Xu, Dunwen Zuo, Julong Yuan and Yingxue Yao
Pages
691-695
DOI
10.4028/www.scientific.net/KEM.315-316.691
Citation
C. H. Lu, J.H. Cao, J. M. Li, X. Y. Li, "Quality Testing for Pressed Raised Character on Metal Label Using GRBF Networks ", Key Engineering Materials, Vols. 315-316, pp. 691-695, 2006
Online since
July 2006
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Price
$32.00
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