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Proceedings Paper

Damage detection in peanut grade samples using chromaticity and luminance
Author(s): Floyd E. Dowell; J. H. Powell
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Paper Abstract

Peanut kernels from grade samples were sorted into damaged and undamaged categories based on their optical characteristics. A machine vision system used grey level information to detect certain types of damage. Also color coordinate information collected from a colorimeter provided additional damage information. Certain damage categories were correctly classified with 95 accuracy. 1 .

Paper Details

Date Published: 1 February 1991
PDF: 5 pages
Proc. SPIE 1379, Optics in Agriculture, (1 February 1991); doi: 10.1117/12.25083
Show Author Affiliations
Floyd E. Dowell, U.S. Dept. of Agriculture (United States)
J. H. Powell, 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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