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Analysis of Visual Quality Attributes of White Shrimp by Machine Vision
Author(s) -
LUZURIAGA DIEGO A.,
BALABAN MURAT O.,
YERALAN SENCER
Publication year - 1997
Publication title -
journal of food science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 150
eISSN - 1750-3841
pISSN - 0022-1147
DOI - 10.1111/j.1365-2621.1997.tb04379.x
Subject(s) - shrimp , white (mutation) , quality (philosophy) , computer vision , artificial intelligence , computer science , fishery , biology , physics , biochemistry , quantum mechanics , gene
An important component of shrimp quality evaluation is determination of visual attributes by trained inspectors. This is subjective, time consuming, and difficult to quantify. An automated device was developed for repeatable, objective measurement of visual quality of shrimp. The device measured the count, uniformity ratio, color, melanosis, and detected foreign objects. Shrimp area viewed by a camera was used to estimate weight after calibration, and count and uniformity ratio was calculated. The system quantified color changes in white shrimp during iced storage. Melanosis was quantified and correlated with the grading of a trained inspector. The method objectively measured visual quality attributes of white shrimp in less than 1 min per sample.