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Proceedings Paper

Image analysis applications for grain science
Author(s): Inna Y. Zayas; James L. Steele
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Paper Abstract

Morphometrical features of single grain kernels or particles were used to discriminate two visibly similar wheat varieties foreign material in wheat hardsoft and spring-winter wheat classes and whole from broken corn kernels. Milled fractions of hard and soft wheat were evaluated using textural image analysis. Color image analysis of sound and mold damaged corn kernels yielded high recognition rates. The studies collectively demonstrate the potential for automated classification and assessment of grain quality using image analysis.

Paper Details

Date Published: 1 February 1991
PDF: 11 pages
Proc. SPIE 1379, Optics in Agriculture, (1 February 1991); doi: 10.1117/12.25086
Show Author Affiliations
Inna Y. Zayas, U.S. Dept. of Agriculture (United States)
James L. Steele, U.S. Dept. of Agriculture (United States)

Published in SPIE Proceedings Vol. 1379:
Optics in Agriculture
James A. DeShazer; George E. Meyer, Editor(s)

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