title: Measurement of meat color using a computer vision system.
abstract: The limits of the colorimeter and a technique of image analysis in evaluating the color of beef, pork, and chicken were investigated. The Minolta CR-400 colorimeter and a computer vision system (CVS) were employed to measure colorimetric characteristics. To evaluate the chromatic fidelity of the image of the sample displayed on the monitor, a similarity test was carried out using a trained panel. The panelists found the digital images of the samples visualized on the monitor very similar to the actual ones (P<0.001). During the first similarity test the panelists observed at the same time both the actual meat sample and the sample image on the monitor in order to evaluate the similarity between them (test A). Moreover, the panelists were asked to evaluate the similarity between two colors, both generated by the software Adobe Photoshop CS3 one using the L, a and b values read by the colorimeter and the other obtained using the CVS (test B); which of the two colors was more similar to the sample visualized on the monitor was also assessed (test C). The panelists found the digital images very similar to the actual samples (P<0.001). As to the similarity (test B) between the CVS- and colorimeter-based colors the panelists found significant differences between them (P<0.001). Test C showed that the color of the sample on the monitor was more similar to the CVS generated color than to the colorimeter generated color. The differences between the values of the L, a, b, hue angle and chroma obtained with the CVS and the colorimeter were statistically significant (P<0.05-0.001). These results showed that the colorimeter did not generate coordinates corresponding to the true color of meat. Instead, the CVS method seemed to give valid measurements that reproduced a color very similar to the real one.
authors.affiliation: Dipartimento di Scienze delle Produzioni Animali, Università degli Studi della Basilicata, Via dell'Ateneo Lucano 10, Potenza 85100, Italy. antonio.girolami@unibas.it
authors.forename: Antonio
authors.initials: A
authors.lastname: Girolami
authors.forename: Fabio
authors.initials: F
authors.lastname: Napolitano
authors.forename: Daniela
authors.initials: D
authors.lastname: Faraone
authors.forename: Ada
authors.initials: A
authors.lastname: Braghieri
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D002417:Cattle; D002645:Chickens; D003116:Color; D003124:Colorimetry / Q000379:methods*; D006801:Humans; D008460:Meat / Q000032:analysis*; D013552:Swine