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Building 3D Statistical Shape Models of Horticultural Products

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Abstract

A method to build a 3D statistical shape model of horticultural products is described. The framework consists of two parts. First, the surfaces of the horticultural products, which are extracted from X-ray CT scans, are registered to obtain meaningful correspondences between the surfaces. In the second part, a statistical shape model is built from these corresponded surfaces, which maps out the variability of the surfaces and allows to generate new, realistic surfaces. The proposed shape modelling method is applied to 30 Jonagold apples, 30 bell peppers, and 52 zucchini. The average geometric registration error between the original instance and the deformed reference instance is 0.015 ± 0.011 m m for the apple dataset, 0.106 ± 0.026 m m for the bell pepper dataset, and 0.027 ± 0.007 m m for the Zucchini dataset. All shape models are shown to be an excellent representation of their specific population, as they are compact and able to generalize to an unseen sample of the population.

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Acknowledgements

This work was supported by the Agency for Innovation by Science and Technology in Flanders (IWT SB 141520 and IWT SBO 120033 TomFood).

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Authors and Affiliations

  1. imec - Vision Lab, Department of Physics, University of Antwerp, Universiteitsplein 1, Building N, 2610, Antwerp, Belgium

    Femke Danckaers, Toon Huysmans & Jan Sijbers

  2. Division of Mechatronics, Biostatistics and Sensors (MeBioS), Department of Biosystems, K.U. Leuven, Kasteelpark Arenberg 30, 3001, Heverlee, Belgium

    Mattias Van Dael, Pieter Verboven & Bart Nicolaï

Authors
  1. Femke Danckaers
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  2. Toon Huysmans
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  3. Mattias Van Dael
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  4. Pieter Verboven
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  5. Bart Nicolaï
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  6. Jan Sijbers
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Correspondence to Femke Danckaers.

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Danckaers, F., Huysmans, T., Dael, M. et al. Building 3D Statistical Shape Models of Horticultural Products. Food Bioprocess Technol 10, 2100–2112 (2017). https://doi.org/10.1007/s11947-017-1979-z

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