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Proceedings Paper

Automated glass-fragmentation analysis
Author(s): Gaile G. Gordon
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Paper Abstract

This paper describes a novel automated inspection process for tempered safety glass. The system is geared toward the European Community (EC) import regulations which are based on fragment count and dimensions in a fractured glass sample. The automation of this test presents two key challenges: image acquisition, and robust particle segmentation. The image acquisition must perform well both for clear and opaque glass. Opaque regions of glass are common in the American auto industry due to painted styling or adhesives (e.g. defroster cables). The system presented uses a multiple light source, reflected light imaging technique, rather than transmitted light imaging which is often used in manual versions of this inspection test. Segmentation of the glass fragments in the resulting images must produce clean and completely connected crack lines in order to compute the correct particle count. Processing must therefore be robust with respect to noise in the imaging process such as dust and glint on the glass. The system presented takes advantage of mathematical morphology algorithms, in particular the watershed algorithm, to perform robust preprocessing and segmentation. Example images and image segmentation results are shown for tempered safety glass which has been painted on the outside edges for styling purposes.

Paper Details

Date Published: 21 February 1996
PDF: 9 pages
Proc. SPIE 2665, Machine Vision Applications in Industrial Inspection IV, (21 February 1996); doi: 10.1117/12.232245
Show Author Affiliations
Gaile G. Gordon, TASC (United States)


Published in SPIE Proceedings Vol. 2665:
Machine Vision Applications in Industrial Inspection IV
A. Ravishankar Rao; Ning Chang, Editor(s)

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