Brand Color Perceptual Distance Rank

Rank actual caller brand reference CIELAB swatches in one white/reference frame by CIE76 distance with stable tie provenance; no invented proprietary brand palette, spectral equivalence or trademark authorization.

Description

Brand swatch ranking can compare caller references within one Lab frame.

Brand swatch ranking can compare caller references within one Lab frame. Stable ties preserve original provenance.^[1]

Enter one same-white Lab reference, aligned nonempty unique nonblank brand labels and 1–128 Lab rows with L 0–100,a/b±200. Sort ascending CIE 76 distance, then original index. Return labels, distances and original indexes.

When to use Brand Color Perceptual Distance Rank

Use Brand Color Perceptual Distance Rank when you need to evaluate the supplied records under the calculation and evidence rules below. No proprietary palette, spectral equivalence or trademark authorization is inferred.

Prepare colors in the stated color space and scale. Use encoded RGB fractions, linear RGB, Lab, xy, byte values or ink percentages exactly as requested; supply caller tolerances and reference conditions.

How to use Brand Color Perceptual Distance Rank and understand its results

Prepare colors in the stated color space and scale. Use encoded RGB fractions, linear RGB, Lab, xy, byte values or ink percentages exactly as requested; supply caller tolerances and reference conditions.
Enter referenceLab, callerBrandLabels, callerBrandLabRows using the field table and calculation rules, then run the tool.
Read rankedCallerBrandLabels, rankedCie76Distances, rankedOriginalIndices. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
referenceLab	Reference lab	list of number	Required
callerBrandLabels	Caller brand labels	list of string	Required
callerBrandLabRows	Caller brand lab rows	list of list of number	Required

distance_i=hypot(referenceLab−swatch_i)

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
rankedCallerBrandLabels	Ranked caller brand labels	list of string
rankedCie76Distances	Ranked cie76 distances	list of number
rankedOriginalIndices	Ranked original indices	list of number

json

{
  "input": {
    "referenceLab": [
      50,
      0,
      0
    ],
    "callerBrandLabels": [
      "Far",
      "Exact"
    ],
    "callerBrandLabRows": [
      [
        60,
        0,
        0
      ],
      [
        50,
        0,
        0
      ]
    ]
  },
  "output": {
    "rankedCallerBrandLabels": [
      "Exact",
      "Far"
    ],
    "rankedCie76Distances": [
      0,
      10
    ],
    "rankedOriginalIndices": [
      1,
      0
    ]
  }
}

Limitations and assumptions

No proprietary palette, spectral equivalence or trademark authorization is inferred.

Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Matrices are limited to 128 rows and 128 entries per row. Numeric lists are limited to 10,000 entries; string lists to 128 strings of at most 128 characters each. The rules above may impose smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.

Alternative or Complementary methods

Use Categorical Minimum Delta-E Pairwise: Categorical color separation can be audited across every palette pair. CIE 76 uses Euclidean distance in one Lab reference frame. For a complementary task, use Brand Hue Variance Degrees Across Assets: Brand hue deviations should use circular offsets around an explicit reference. Opposing observations can leave the circular mean unavailable.

References

Brand Color Perceptual Distance Rank — tool.io

Similar or alternative tools

Categorical Minimum Delta-E Pairwise
Categorical color separation can be audited across every palette pair. CIE 76 uses Euclidean distance in one Lab reference frame.
Brand Hue Variance Degrees Across Assets
Brand hue deviations should use circular offsets around an explicit reference. Opposing observations can leave the circular mean unavailable.