Damage detection in peanut grade samples using chromaticity and luminance

Floyd E. Dowell; J. H. Powell

doi:10.1117/12.25083

1 February 1991 Damage detection in peanut grade samples using chromaticity and luminance

Floyd E. Dowell, J. H. Powell

Proceedings Volume 1379, Optics in Agriculture; (1991) https://doi.org/10.1117/12.25083
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States

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 .

Citation Download Citation

Floyd E. Dowell and J. H. Powell "Damage detection in peanut grade samples using chromaticity and luminance", Proc. SPIE 1379, Optics in Agriculture, (1 February 1991); https://doi.org/10.1117/12.25083

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