Hyperspectral database of fruits and vegetables

J Opt Soc Am A Opt Image Sci Vis. 2018 Apr 1;35(4):B256-B266. doi: 10.1364/JOSAA.35.00B256.


We have built a hyperspectral database of 42 fruits and vegetables. Both the outside (skin) and inside of the objects were imaged. We used a Specim VNIR HS-CL-30-V8E-OEM mirror-scanning hyperspectral camera and took pictures at a spatial resolution of ∼57 px/deg by 800 pixels at a wavelength resolution of ∼1.12 nm. A stable, broadband illuminant was used. Images and software are freely available on our webserver (http://www.allpsych.uni-giessen.de/GHIFVD; pronounced "gift"). We performed two kinds of analyses on these images. First, when comparing the insides and outsides of the objects, we observed that the insides were lighter than the skins, and that the hues of the insides and skins were significantly correlated (circular correlation=0.638). Second, we compared the color distribution within each object to corresponding human color discrimination thresholds. We found a significant correlation (0.75) between the orientation of ellipses fit to the chromaticity distributions of our fruits and vegetables with the orientations of interpolated MacAdam discrimination ellipses. This indicates a close relationship between sensory processing and the characteristics of environmental objects.

MeSH terms

  • Color Perception / physiology*
  • Databases, Factual*
  • Fruit*
  • Humans
  • Image Processing, Computer-Assisted
  • Light
  • Photography / instrumentation
  • Spectrum Analysis*
  • Vegetables*