Computer Vision-Based Sorting of Atlantic Salmon (Salmo salar) Fillets According to Their Color Level

Authors

  • E. Misimi,

    1. Authors Misimi, Mathiassen, and Erikson are with SINTEF Fisheries and Aquaculture, N-7465 Trondheim, Norway. Author Misimi is with Dept. of Engineering Cybernetics, NTNU, N-7491 Trondheim, Norway. Direct inquiries to author Misimi (E-mail: ekrem.misimi@sintef.no).
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  • J.R. Mathiassen,

    1. Authors Misimi, Mathiassen, and Erikson are with SINTEF Fisheries and Aquaculture, N-7465 Trondheim, Norway. Author Misimi is with Dept. of Engineering Cybernetics, NTNU, N-7491 Trondheim, Norway. Direct inquiries to author Misimi (E-mail: ekrem.misimi@sintef.no).
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  • U. Erikson

    1. Authors Misimi, Mathiassen, and Erikson are with SINTEF Fisheries and Aquaculture, N-7465 Trondheim, Norway. Author Misimi is with Dept. of Engineering Cybernetics, NTNU, N-7491 Trondheim, Norway. Direct inquiries to author Misimi (E-mail: ekrem.misimi@sintef.no).
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Abstract

ABSTRACT:  Computer vision method was used to evaluate the color of Atlantic salmon (Salmo salar) fillets. Computer vision-based sorting of fillets according to their color was studied on 2 separate groups of salmon fillets. The images of fillets were captured using a digital camera of high resolution. Images of salmon fillets were then segmented in the regions of interest and analyzed in red, green, and blue (RGB) and CIE Lightness, redness, and yellowness (Lab) color spaces, and classified according to the Roche color card industrial standard. Comparisons of fillet color between visual evaluations were made by a panel of human inspectors, according to the Roche SalmoFan™ lineal standard, and the color scores generated from computer vision algorithm showed that there were no significant differences between the methods. Overall, computer vision can be used as a powerful tool to sort fillets by color in a fast and nondestructive manner. The low cost of implementing computer vision solutions creates the potential to replace manual labor in fish processing plants with automation.

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