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Proceedings Paper

Machine vision-based evaluation of mixture percentages for powder blending processes
Author(s): Joseph Wilder; I. Marsic; Fernando J. Muzzio; Augustine Tsai; S. Weiner; C. Wightman
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Paper Abstract

Quantitative analysis of the powder blending process is important in many industries, e.g. pharmaceutical, glass, food products. Inefficient blending can lead to inhomogeneous powder mixtures and unacceptable product variability. A new method has been devised by F.J. Muzzio and his students to characterize the uniformity of powder mixtures by solidifying samples of the mixtures without disturbing their structure, and subjecting them to machine vision analysis. The key components of the mixture are colored and, with appropriate illumination, the mixture percentage is directly related to video signal intensity. This paper reviews the machine vision algorithms required to perform the analysis, focussing in particular on the real-time hardware configurations that enable significant amounts of data to be collected for use in evaluation of the integrity of the blending process.

Paper Details

Date Published: 13 September 1995
PDF: 7 pages
Proc. SPIE 2598, Videometrics IV, (13 September 1995); doi: 10.1117/12.220900
Show Author Affiliations
Joseph Wilder, Rutgers Univ. (United States)
I. Marsic, Rutgers Univ. (United States)
Fernando J. Muzzio, Rutgers Univ. (United States)
Augustine Tsai, Rutgers Univ. (United States)
S. Weiner, Rutgers Univ. (United States)
C. Wightman, Rutgers Univ. (United States)

Published in SPIE Proceedings Vol. 2598:
Videometrics IV
Sabry F. El-Hakim, Editor(s)

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