1 February 1991 Damage detection in peanut grade samples using chromaticity and luminance
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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
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 .
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Floyd E. Dowell, J. H. Powell, "Damage detection in peanut grade samples using chromaticity and luminance", Proc. SPIE 1379, Optics in Agriculture, (1 February 1991); doi: 10.1117/12.25083; https://doi.org/10.1117/12.25083

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