Final answer:
To calculate the total color difference between two food samples, one needs to convert color measurements from RGB to various color spaces like CIEL*a*b* and HSV, calculate chroma and hue angle for CIEL*a*b* values, and summarize all values in a table. Precise color identification may require complex conversions and specialized equipment.
Step-by-step explanation:
Understanding Color Differences and Conversions
To calculate the total color difference between two food samples, one must understand the conversion between different color models such as RGB, CIEL*a*b*, and HSV. Each model has its own relevance. The RGB model represents the way colors are produced by mixing red, green, and blue light as is common in digital displays. The CIEL*a*b* model, on the other hand, is used to provide a colorimetric representation that is more aligned with human vision. The HSV model represents colors in terms of hue, saturation, and value (brightness).
Calculating Chroma and Hue Angle from CIEL*a*b*
Chroma (C*) and hue angle (H*) are calculated from the a* and b* values of the CIEL*a*b* color space. The chroma (C*) is the saturation of the color and can be calculated using the formula C* = sqrt(a*^2 + b*^2). The hue angle (H*), representing the type of color, is calculated by H* = atan2(b*, a*), where atan2 is the two-argument arctangent function.
Conversion Between Color Models
Conversion processes include converting RGB values to CIEL*a*b*, then to CIE XYZ, and finally to CIE xyY color spaces. Each conversion step requires complex formulas and might utilize intermediary color spaces or involve normalization based on specific illuminant and observer conditions.
The process of identifying a color name, dominant wavelength, and purity can be intricate, depending on color matching functions and spectral distributions. When precise data or equipment is not available, this process can be problematic.
In conclusion, summarizing all values on one table would consolidate data from RGB, HSV, CIEL*a*b*, chroma, hue, and CIE xyY transformations for a comprehensive understanding of a sample's color characteristics. Practically, this task involves using specialized software or mathematical calculations that consider the specifics of human color perception and light's physical properties.