Neural network classification of Fraunhofer diffraction patterns for inspection of fine pitch electronic components

David J. Search; Clifford Allan Hobson; John T. Atkinson; Jeremy David Pearson

doi:10.1117/12.196082

23 November 1994 Neural network classification of Fraunhofer diffraction patterns for inspection of fine-pitch electronic components

David J. Search, Clifford Allan Hobson, John T. Atkinson, Jeremy David Pearson

Author Affiliations +

Proceedings Volume 2249, Automated 3D and 2D Vision; (1994) https://doi.org/10.1117/12.196082
Event: Optics for Productivity in Manufacturing, 1994, Frankfurt, Germany

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.

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David J. Search, Clifford Allan Hobson, John T. Atkinson, and Jeremy David Pearson "Neural network classification of Fraunhofer diffraction patterns for inspection of fine-pitch electronic components", Proc. SPIE 2249, Automated 3D and 2D Vision, (23 November 1994); https://doi.org/10.1117/12.196082

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