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Proceedings Paper

Neural network classification of Fraunhofer diffraction patterns for inspection of fine pitch electronic components
Author(s): David J. Search; Clifford Allan Hobson; John T. Atkinson; Jeremy David Pearson
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Paper Abstract

This paper describes research into a non-contact system for the inspection of fine pitch electronic components on manufactured electronic assemblies. A far-field diffraction pattern from the leads of a tape automated bonding component is captured and stored on a frame store. The diffraction pattern is statistically represented and then classified using an artificial neural network. Results from simulation and experimentation show the feasibility of the technique.

Paper Details

Date Published: 23 November 1994
PDF: 8 pages
Proc. SPIE 2249, Automated 3D and 2D Vision, (23 November 1994); doi: 10.1117/12.196082
Show Author Affiliations
David J. Search, Liverpool John Moores Univ. (United Kingdom)
Clifford Allan Hobson, Liverpool John Moores Univ. (United Kingdom)
John T. Atkinson, Liverpool John Moores Univ. (United Kingdom)
Jeremy David Pearson, Liverpool John Moores Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 2249:
Automated 3D and 2D Vision
Rolf-Juergen Ahlers; Donald W. Braggins; Gary W. Kamerman, Editor(s)

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