Machine vision-based evaluation of mixture percentages for powder blending processes

Joseph Wilder; I. Marsic; Fernando J. Muzzio; Augustine Tsai; S. Weiner; C. Wightman

doi:10.1117/12.220900

13 September 1995 Machine-vision-based evaluation of mixture percentages for powder blending processes

Joseph Wilder, I. Marsic, Fernando J. Muzzio, Augustine Tsai, S. Weiner, C. Wightman

Proceedings Volume 2598, Videometrics IV; (1995) https://doi.org/10.1117/12.220900
Event: Photonics East '95, 1995, Philadelphia, PA, United States

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.

Citation Download Citation

Joseph Wilder, I. Marsic, Fernando J. Muzzio, Augustine Tsai, S. Weiner, and C. Wightman "Machine-vision-based evaluation of mixture percentages for powder blending processes", Proc. SPIE 2598, Videometrics IV, (13 September 1995); https://doi.org/10.1117/12.220900

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