Seeing Color as Data, Not Just Perception
COCORY JOURNAL 02-5
The fact that skin color can be measured numerically is fascinating.
We can look at lightness through L*, examine the degree of redness and yellowness through a* and b*, and use b-a to observe the relationship between these two color components.
But in an actual personal color analysis, the more important question comes next.
How should we use these numbers?
Measuring skin does not automatically determine which colors will suit a person.
Data is not an answer that defines a person as a single type. It is a reference that helps us understand visual observation and comparison more precisely.
Measurement Is the Beginning of Observation
When we look at someone’s skin, we perceive many characteristics at once.
We may notice how light or dark the skin appears, how much redness or yellowness is visible, and whether the overall color impression feels more pronounced or subdued.
But visual judgment is affected by the surrounding environment.
The color and intensity of light, nearby colors, the background, makeup, and even the colors we have just seen can influence how skin appears.
Measurement allows us to separate some characteristics of the skin’s current color from this complex visual environment and examine them numerically.
For example:
- L* can indicate the current level of skin lightness.
- a* can indicate the degree of the red component.
- b* can indicate the degree of the yellow component.
- b-a can help us examine the relative relationship between redness and yellowness.
These values are not a conclusion that says, “This person has this type of skin.”
They are a starting point for understanding how the skin color we are currently observing is structured.
One Number Cannot Explain a Person
Imagine two people with the same b-a value.
Would their skin necessarily look the same?
Not at all.
For example, skin measured at a*=20 and b*=26 and skin measured at a*=4 and b*=10 both produce a b-a value of 6.
Yet the magnitude of their color components is very different.
If their L* values are also different, the visual impression of their skin may become even more distinct.
This is why skin color data should never be interpreted through a single number alone.
Values such as L*, a*, b*, and b-a are not independent answers. They are pieces of information that need to be read together.
And these measurements describe the current state of skin color. They do not directly tell us how that skin color will appear in relation to different surrounding colors.
Skin Color and “Flattering Color” Are Different Questions
Two questions are often treated as if they were the same in personal color analysis:
“What color is my skin?”
and
“Which colors look good on me?”
The questions are related, but they are not identical.
Skin measurement can help us examine the first question more objectively.
The second question, however, requires comparison.
When different colors are placed near the face, we need to observe how the color appearance of the skin changes in relation to them.
Does the skin appear lighter or darker?
Does redness become more or less noticeable?
Does yellowness appear stronger or weaker?
Does the overall skin color appear more balanced or less balanced?
These are color-related changes that become visible through comparison.
This means that it is difficult to create a simple formula in which one particular skin value directly corresponds to a particular clothing or makeup color.
Skin color data and color-response observations need to be understood separately.
Measuring skin helps us understand its current color.
Comparing colors allows us to observe how that color appears and changes in relation to surrounding colors.
This Is Why Analysis Requires Comparison
A single measurement can provide information about a person’s current skin color.
But it cannot show us what will happen when different colors are placed near that person’s face.
This is where comparison begins.
Colors with different characteristics are applied near the face, and the resulting color changes are observed repeatedly.
With one color, the skin may appear relatively even. With another, redness or yellowness may become more noticeable.
The apparent brightness of the skin may change, and the balance among its visible color components may also appear different.
The important point is not to draw a conclusion from one impression.
Change the color. Compare again. Look for color changes that appear consistently.
This is why comparison is fundamental to personal color analysis.
Data Does Not Replace the Eye. It Trains It.
As color measurement technology becomes more sophisticated, it can be tempting to imagine that machines will eventually make every decision for us.
COCORY sees the role of data differently.
Data does not exist to eliminate observation.
Instead, it helps us understand more precisely what we are actually seeing.
If skin appears slightly more yellow, we can examine how that observation relates to its b* value.
If two skin colors appear similar, we can examine how their L*, a*, and b* values differ.
If a color-related change in the skin is observed with a particular color, we can compare that response repeatedly against other colors.
Through this process, subjective impressions can gradually become more specific observations.
Seeing and measuring are not competing approaches.
Measurement supports observation, while observation interprets relationships that numbers alone cannot contain.
[IMAGE 3 — HERE]
We Do Not Fit People to Numbers. We Use Numbers for People.
One of the greatest risks in data-based analysis is allowing the number to come before the person.
If a person is assigned to a predefined category simply because a particular measurement falls within a certain range, measurement can actually reduce the opportunity to observe the individual in front of us.
COCORY approaches skin color data from the opposite direction.
We look at the person.
We measure.
We apply different colors.
We compare the color changes.
We observe again.
And when necessary, we return to the data.
In this process, numbers do not force a conclusion. They become tools for improving the precision of observation.
Ultimately, the subject of analysis is not a number.
It is a person.
From Data, Back to the Person
Throughout Series 02, we began by asking what it means to “see” skin color.
We then explored how skin color can be measured, how those measurements can be read, and why familiar descriptions of skin do not always correspond neatly to measurable color values.
We also considered how the conditions in which we observe skin can affect the color we perceive.
All of these discussions lead to one idea.
Measurement is not meant to simplify people. It is meant to help us see them with greater precision.
Skin color is too complex to be fully explained by a single word.
And it is even more complex than a single number can define.
That is why we observe, measure, and compare.
And then we return to the person.
Data becomes meaningful not at the moment a number is produced,
but when that number helps us see a person more accurately.
NEXT JOURNAL
Once we move beyond measuring and comparing skin color, another question emerges: how can we analyze the broader relationships between color and the individual?
In the next COCORY JOURNAL series, we will explore the relationship between people and color from a new perspective.
COCORY Color
사람을 위한 색의 기준을 세우다.
Making Color Work for Everyone
