23 November 1994 Neural network classification of Fraunhofer diffraction patterns for inspection of fine-pitch electronic components
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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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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); doi: 10.1117/12.196082; https://doi.org/10.1117/12.196082
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