4.5.1.
Interpretation of total colour differences between tile and cake
colours
Ultimately, the goal of computer colour matching is to achieve a good visual match. The convenience and speed of computer colour matching is balanced against the need for a colour difference index applied to the computed match which represents the degree of the visual match between the colours of two samples. This discussion is focused largely on the ΔE*ab,10
differences between tile and cake colours, rather than on both the ΔE*ab,10 and ΔE00 differences,
because tolerance limits are available for ΔE*ab,10 albeit mostly from non-food industries. Put
simply, tolerance limits indicate the limit of an acceptable colour match. These limits can vary according to the application: while a ΔE*ab,10 of three units or more is considered a visually
unacceptable match in non-food applications (Francis and Clydesdale, 1975), the tolerance limit can be as low as less than one ΔE*ab,10 unit in the automotive industry (for a commercial match).
In the middle of this range, a ΔE*ab,10 of two units can indicate a perceptible difference (Francis
and Clydesdale, 1975).
The physical differences between target and matching systems (tile and cake respectively) were very likely to influence how the differences in colour between them would be perceived, despite best matching efforts. Differences in the range of colours (i.e. the colour gamut) that can be achieved in each system also need to be taken into account. In 3D colour food printing also, target and match might not necessarily be viewed side-by-side, and the perception of each colour voxel might be influenced by the colours of the surrounding voxels. Therefore, applying a tolerance limit in this study which is higher than that for a visually perceptible difference was reasonable. Without the benefit of having established an appropriate tolerance limit for use in this study with a panel of observers, this study was instead guided by values from the literature. The tolerance limit chosen was a ΔE*ab,10 difference of three units, which was also used by
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wines. It should be noted however that while this limit was established for red wines on the basis of both observer and instrumental data, for the muffin work the reference for the three-unit limit on ΔE*ab,10 was also Francis and Clydesdale (1975) with no explanation given as to
whether this tolerance limit is actually suitable for muffins.
Eight of the original 24 tile target L*10a*10b*10 colours (across SCI and SCE) were within the
cake colour gamut. Of these eight colours, seven had a ΔE*ab,10 difference between tile colour
and measured cake colour of more than three units. For SCI and SCE tile colours that were originally out-of-gamut, the ΔE*ab,10 differences between tile colour and measured cake colour
ranged from 3.4 to 37.1. As expected, these latter differences were comparatively large as a result of having to adjust concentration outputs from colorimetric matching. Visual inspection of the matches between tile and cake, for the SCI colours at least (Figure 4.8) suggests that these matches are closer than are indicated by their ΔE*ab,10 differences, and that new, more
appropriate tolerance limits, or alternatively another colour difference index, are needed. The tolerance level of three ΔE*ab units has typically been used to compare samples of the same
type, and might be too strict to compare samples such as the tiles and cakes, which differ physically. A new tolerance limit could take into account that in baked goods, measured colours are found to be darker than visually perceived colour; instrumentally-measured colour averages the effect of surface crumb texture by including the bubbles, yet visual colour is seen as separate from the bubbles (MacDougall, 2002b). Formulae for the total difference between samples that differ in colour and surface texture have been proposed (Huang et al., 2010), which are based on physical measurements of the samples, and which could be used to predict visual differences.
4.5.1.1.The use of ΔE00 vs. ΔE*ab,10
The need for a more precise colour difference index, such as ΔE00, in food applications warrants
further consideration (MacDougall, 2002a). Measures of ΔE00 were included in this study
because ΔE00 is the most recent colour difference formula, providing an improvement on
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usually smaller than the ΔE*ab,10 difference for a given comparison between two samples, but
the units for the two indices are on different scales. Strictly speaking, ΔE00 applies to uniform
surface colours with ΔE*ab,10 differences below five units. With the exception of a small subset
of the ΔE*ab,10 differences between tile colours and measured cake colours being less than five
units, the experimental conditions in this study differ to the reference conditions to which ΔE00
applies. This will affect the performance of ΔE00 as an indicator of visually-perceived colour
differences ([CIE] International Commission on Illumination, 2001).
4.5.2.
Differences in lightness, hue and chroma
The ΔE*ab,10 and ΔE00 formulae give an index of total colour difference, incorporating lightness,
hue and chroma differences, but do not indicate the relative contributions of each. Table 4.4 also shows the ΔE*ab,10 differences between tile colours and measured cake colours expressed in
terms of lightness, chroma and hue differences. For Cyan and Orange, ΔE*ab,10 stemmed
predominantly from hue and chroma differences. Lightness difference was the largest contributor for Deep Grey SCE, whereas lightness and chroma largely influenced the difference for Deep Blue and Red SCE. Yellow colour difference was most influenced by lightness and chroma differences, to a similar extent for the SCI and SCE colours; the SCI and SCE colours also displayed similar ΔE*ab,10 differences between tile and cake L*10a*10b*10. For future
reference, ΔE00, like ΔE*ab,10, can also be expressed as separate lightness, hue and chroma
differences.
Tiles and cakes could differ also in the relative importance of lightness, chroma and hue in the visual perception of their colours, with implications for interpreting the degree of overall colour matching between tiles and cakes. Even within foods, hue is much more important visually for some foods (such as tomato juice), and lightness more so for others (for example, roasted ground coffee and canned tuna) (Francis and Clydesdale, 1975). Furthermore, humans are able to better detect changes in hue and lightness, but less so changes in chroma. With the parametric factors in the formula for ΔE00 kept as kL = kC = kH = 1 (as in reference experimental
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colours and cake colours in this study. Further work is needed to determine parametric factors more appropriate to comparing food colours to standards.
4.5.3.
The appropriateness of using tile colours as matching targets
For glossy materials such as the tiles, their colours measured with the SCE may have been the more appropriate as matching targets; the exclusion of specular reflections is equivalent to an observer being able to see mirror reflections and having to move the sample at different angles to observe the colour (Berns, 2000). The conditions in which the visual equivalent of SCI measurements can occur are rare in reality (Berns, 2000).
The tiles may appear to have been an unusual choice of target for colour matching; compared to cake colours, tile colours were uniform and glossy, with more than half being out-of-gamut. The tiles were not specially procured for this project; a set was available within the Institute and therefore a set of useful colour standards was already accessible. Out-of-gamut colours as matching targets were not to be avoided as the problem of out-of-gamut colours will be encountered in the transcribing of screen or image colours to food colours by the 3D colour food printer.