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Color of Salmon Fillets By Computer Vision and Sensory Panel

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Abstract

A computer vision method was developed and used to assign color score in salmon fillet according to SalmonFan™ card. The methodology was based on the transformation of RGB to L*a*b* color space. In the algorithm, RGB values assigned directly to each pixel by the camera in the salmon fillet image, were transformed to L*a*b* values, and then matched with other L*a*b* values that represent a SalmonFan score (between 20 and 34). Colors were measured by a computer vision system (CVS) and a sensorial panel (eight panelists) under the same illumination conditions in ten independent sets of experiments. Errors from transformation of RGB to L*a*b* values by the CVS were 2.7%, 1%, and 1.7%, respectively, with a general error range of 1.83%. The coefficient of correlation between the SalmonFan score assigned by computer vision and the sensory panel was 0.95. Statistical analysis using t test was performed and showed that there were no differences in the measurements of the SalmonFan score between both methods (t c = 1.65 ≤ t = 1.96 at α = 0.05%). The methodology presented in this paper is very versatile and can potentially be used by computer-based vision systems in order to qualify salmon fillets based on color according to the SalmonFan card.

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Acknowledgment

This research was supported by the project FONDECYT–Chile number 1060355.

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Authors and Affiliations

  1. Department of Science and Food Technology, Universidad de Los Lagos, Av. Fushlocher 1305, Osorno, Chile

    R. A. Quevedo

  2. Department of Chemical Engineering and Bioprocesses, Pontificia Universidad Católica de Chile, P.O. Box 306, Santiago, Chile

    J. M. Aguilera

  3. Department of Food Science and Technology, Universidad de Santiago de Chile (USACH), Av. Ecuador, 3769, Santiago, Chile

    F. Pedreschi

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  1. R. A. Quevedo
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  2. J. M. Aguilera
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  3. F. Pedreschi
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Correspondence to R. A. Quevedo.

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Quevedo, R.A., Aguilera, J.M. & Pedreschi, F. Color of Salmon Fillets By Computer Vision and Sensory Panel. Food Bioprocess Technol 3, 637–643 (2010). https://doi.org/10.1007/s11947-008-0106-6

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  • DOI: https://doi.org/10.1007/s11947-008-0106-6

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