Color machine vision-colorimeter

Correlation Between Color Machine Vision and Colorimeter for Food Applications... 

Figure 5. The color machine vision system and the colorimeter have an R value better than 0.98, in determining color differences between sample colors and a white standard.

Correlation was established between the colors of food samples measured by the colorimeter color and the color machine vision system. The correlation coefficients between L a b color parameters for beef and carrots obtained from the two instruments can be seen in Table 2. For all the data collected, a high correlation was observed (R > = 0.98). The established correlation makes it possible to verify CMVS s color measurement accuracy of colors that are not available from published color standards. Furthermore, the correlations between the CMVS and colorants in food systems can also be inferenced based on established correlations between colorimeter measurements and colorant contents. 

Figure 8. Excellent agreement was found between the color machine vision and the colorimeter measured carrot puree colors. The largest disagreement was less than 2 CIE units, while most differences are less than 0.5 CIE unit.

In-line/on-line feedback control of color of food during processing can improve not only color quality but also color related quality such as texture and appearance. To do this, there are three major aspects development of an in-line/on-line color sensor understanding of color change kinetics and establish correlations between instrumental measured and sensory panel perceived colors of foods. In this research, we have chosen color machine vision technology for the measurement of colors of food due to its superior spatial resolution over conventional instruments such as colorimeter or spectrophotometer. Relationships between measured colors and corresponding principal chemical markers were established for the model food systems. We have also found excellent correlations between the color machine vision system (CMVS) measured and a sensory panel determined colors of food samples (Ling and Tepper, 1995). We believed that a CMVS can be used for food process control to ensure color quality as perceived by consumers. 

A CMVS was designed and evaluated on colors perceived by human. The machine vision measured tri-stimulus values in R,G,B color coordinate were transformed to L a b color space for better representation of human perceived colors. The CMVS measurements were evaluated using Munsell standard color chips, a colorimeter, and a sensory panel. Excellent correlations were found between the CMVS and the colorimeter, which is designed to quantify human perceived colors. The CMVS s ability in quantifying human perceived colors was evidenced by accurate measurement of Munsell standard color chips and the excellent correlations with the sensory panel perceived colors (R>0.90). From the experiments, it was possible to resolve up to 0.7 CIE unit color difference of the tested colors. 

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