Dipartimento di Scienze delle Produzioni Animali, Università degli Studi della Basilicata, Via dell'Ateneo Lucano 10, Potenza 85100, Italy.
Meat Sci. 2013 Jan;93(1):111-8. doi: 10.1016/j.meatsci.2012.08.010. Epub 2012 Aug 17.
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.
研究了比色计和图像分析技术在评估牛肉、猪肉和鸡肉颜色方面的局限性。采用美能达 CR-400 比色计和计算机视觉系统 (CVS) 测量比色特性。为了评估监视器上显示的样品图像的色度保真度,使用经过培训的小组进行了相似性测试。小组成员发现监视器上可视化的样品数字图像与实际样品非常相似(P<0.001)。在第一次相似性测试中,小组成员同时观察实际肉样和监视器上的样品图像,以评估它们之间的相似性(测试 A)。此外,小组成员被要求评估两种颜色之间的相似性,一种颜色由 Adobe Photoshop CS3 软件生成,使用比色计读取的 L、a 和 b 值,另一种颜色由 CVS 生成(测试 B);还评估了监视器上可视化的样本与两种颜色中哪一种更相似(测试 C)。小组成员发现数字图像与实际样本非常相似(P<0.001)。至于 CVS 和比色计生成的颜色之间的相似性(测试 B),小组成员发现它们之间存在显著差异(P<0.001)。测试 C 表明,监视器上的样本颜色与 CVS 生成的颜色比与比色计生成的颜色更相似。CVS 和比色计获得的 L、a、b、色调角和色度值之间存在统计学差异(P<0.05-0.001)。这些结果表明比色计没有生成与肉的真实颜色相对应的坐标。相反,CVS 方法似乎提供了有效的测量值,可以复制非常接近真实颜色的颜色。