AQC0692 | NAN-COL000258

Nanopublication — Computational Image Analysis - AQC0692

B Major - Research on Harmony - Variation 2

Claim 1: Computational Image Analysis - AQC0692

Computational analysis of the photograph of the artwork B Major - Research on Harmony - Variation 2 (AQC0692) [1] by Arnaud Quercy [2], according to IDS-CMP-2025 [3], on an image 1000 pixels on its longer side, on 2025-10-03. Each colour is located in the Munsell system and named according to the ISCC-NBS system (267 names, National Bureau of Standards, 1976). The image divides into 22 flat areas. The largest are dark grayish olive (13%), grayish yellow (12%) and moderate olive green (10%). Among the others, those that stand out most sharply from their surroundings are pale orange yellow at the bottom left (0.9%), pale yellow at the top left (3.9%) and grayish olive green at the top (0.1%). By colour name family: yellow 33%, olive 15%, gray 12%, olive green 10.0%, brown 5.1%, olive gray 3.9%, purple 3.7%, yellow brown 3.5%, blue 2.8%, olive brown 2.3%, green 2.1%, yellow green 1.9%, orange yellow 1.4% and reddish purple 1.3%.

Context

Analysis performed according to IDS-CMP-2025 [3]: (a) colours named by Munsell and ISCC-NBS, areas and flat areas, (b) texture, (c) brightness and contrast, (d) spatial distribution. Source image: 2043x2043 pixels. Analysis date: 2025-10-03.

A) Color Analysis

Flat areas

Ranked by contrast with their surroundings (CIEDE2000). Strokes thinner than 10 pixels are excluded (0).

Rank Colour ISCC-NBS name Munsell Area Contrast Position
1 E1CFA5 pale orange yellow 0.9Y 8.3/3.4 0.9% 62.6 at the bottom left
2 E2CB94 pale yellow 2.8Y 8.2/4.4 3.9% 41.5 at the top left
3 474D31 grayish olive green 4.8GY 3.1/2.5 0.1% 40.1 at the top
4 8E727F grayish purple 5.0RP 5.0/2.6 2.8% 37.9 at the top
5 D2B94B strong yellow 5.7Y 7.6/8.0 2.5% 37.9 in the centre
6 515B37 moderate olive green 3.4GY 3.7/3.5 0.2% 37.2 in the centre
7 62809C grayish blue 1.2PB 5.3/4.3 0.1% 34.7 in the centre
8 747066 light grayish olive 0.6GY 4.7/1.3 9.2% 28.1 on the right
9 CBB27D grayish yellow 3.1Y 7.3/4.5 6.3% 27.1 on the right
10 B69D47 dark yellow 5.0Y 6.4/6.7 0.1% 26.5 in the centre
11 9194A6 pale purple 9.1PB 6.1/2.4 5.3% 25.0 at the bottom right
12 D7C093 grayish yellow 4.1Y 7.9/3.6 12% 24.4 on the right
13 D8CB49 brilliant greenish yellow 7.5Y 8.1/8.7 7.0% 22.9 in the centre
14 6C8753 moderate yellow green 6.7GY 5.1/4.4 0.2% 22.9 in the centre
15 405643 dark grayish green 10.0GY 3.3/2.2 2.0% 20.1 in the centre
16 546042 moderate olive green 6.4GY 3.9/3.1 10% 18.3 at the top left
17 AE9F4F dark yellow 6.6Y 6.3/5.9 3.2% 18.0 at the top
18 36322B dark grayish olive 0.6GY 2.1/0.9 13% 16.1 at the bottom left
19 B4882F dark yellow 2.4Y 5.9/7.9 0.5% 15.2 in the centre
20 5B483C dark grayish yellow brown 9.6YR 3.3/1.9 5.1% 11.9 at the bottom
21 716E70 purplish gray 7.8P 4.6/1.3 10% 10.4 at the bottom
22 767833 moderate yellow green 2.5GY 4.9/5.5 5.6% 10.1 on the left

Colour name families

Family Area
yellow 33%
olive 15%
gray 12%
olive green 10.0%
brown 5.1%
olive gray 3.9%
purple 3.7%
yellow brown 3.5%
blue 2.8%
olive brown 2.3%
green 2.1%
yellow green 1.9%
orange yellow 1.4%
reddish purple 1.3%
violet 1.0%
red 0.6%

B) Texture Analysis

Metric Value
Global Roughness 0.2
Mean Local Roughness 0.015
Roughness Uniformity 0.025
Edge Density 0.051
Mean Gradient Magnitude 0.108
Gradient Variance 0.051
Gradient Smoothness 0.0
Directional Coherence 0.146
Pattern Complexity 0.114
Pattern Repetition 1.0
Detail Frequency Ratio 0.654
Spatial Variation 0.132
Texture Consistency 0.638

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.504
Brightness Variance 0.2
Brightness Uniformity 0.602
Brightness Skewness 0.059
Brightness Entropy 7.221
Rms Contrast 0.2
Michelson Contrast 1.0
Weber Contrast 0.716
Mean Local Contrast 0.015
Contrast Uniformity 0.0
Dynamic Range 0.996
Effective Dynamic Range 0.604
Shadow Percentage 22.247
Midtone Percentage 46.189
Highlight Percentage 31.564
Shadow Clipping 0.002
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.02
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.108
Contrast Clustering 0.362

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.765
Color Clustering 0.619
Color Transition Smoothness 0.716
Transition Uniformity 0.66
Sharp Transition Ratio 0.1
Transition Directionality 0.157
Mean Saturation 0.311
Saturation Variance 0.033
Low Saturation Ratio 0.482
Medium Saturation Ratio 0.491
High Saturation Ratio 0.027
Saturation Clustering 0.999
Hue Concentration 0.923
Complementary Balance 0.007
Analogous Dominance 0.964
Temperature Bias 0.716

Methodology

Computational analysis of a photograph of the artwork, reduced to 1,000 pixels on its longer side and filtered by a 3×3 median to remove grain. Colours: each pixel (sRGB rounded to 5 bits per channel) receives its Munsell notation and ISCC-NBS name from a table computed once from published data (Munsell renotation; ISCC-NBS blocks, NBS Special Publication 440, 1976), never from the artworks. Flat areas: connected regions of one name, merged with their neighbours while the CIEDE2000 difference between their mean colours stays below 10; an area is kept from 0.05% of the image; contrast with the surroundings measured 4 to 12 pixels from the edge. Texture: intensity standard deviation, local standard deviation, edge density (Canny), local binary patterns. Brightness: mean, variance, RMS, Michelson and local contrast, shadow / midtone / highlight distribution. Distribution: spatial coherence, transitions, saturation. Methods are deterministic and reproducible. Limits: the measurement concerns the photograph, including its lighting and white balance; two neighbouring areas less than 10 apart are merged.

References

  1. [1] Quercy, A. (2024). B Major - Research on Harmony - Variation 2 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0692.html
  2. [2] Quercy, A. (2025). ORCID https://orcid.org/0009-0000-2662-7790
  3. [3] Quercy, A. (2026). Computational Image Analysis Standard. https://ideamorphism.org/en/measurements/2025/11/ids-cmp-2025-computational-image-analysis-standard-5dq9.html

Epistemic profile

Claim typecomputational analysis
Voicethird person
Epistemic statusempirical measurement
Methodologycomputational analysis
Certaintyhigh

Checksum (SHA-256)

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