AQC0699 | NAN-COL000252

Nanopublication — Computational Image Analysis - AQC0699

D Major - Research on Harmony - Variation 4

Claim 1: Computational Image Analysis - AQC0699

Computational analysis of the photograph of the artwork D Major - Research on Harmony - Variation 4 (AQC0699) [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 23 flat areas. The largest are deep orange yellow (31%), dark olive brown (14%) and brownish orange (12%). Among the others, those that stand out most sharply from their surroundings are light yellowish brown on the right (0.2%), moderate yellowish green in the centre (0.3%) and moderate orange at the bottom right (2.6%). By colour name family: orange yellow 31%, brown 20%, orange 18%, yellow 8.7%, black 5.6%, olive brown 4.3%, olive black 4.2%, yellow brown 2.6%, olive 1.7%, green 1.5% and olive green 1.0%.

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: 2548x2548 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 201C17 dark olive brown 1.2Y 1.1/1.0 14% 50.4 on the right
2 DAAD74 light yellowish brown 8.5YR 7.3/5.9 0.2% 40.0 on the right
3 5A8B55 moderate yellowish green 9.4GY 5.3/5.9 0.3% 32.1 in the centre
4 E69366 moderate orange 3.3YR 6.7/8.1 2.6% 30.9 at the bottom right
5 324E34 dark yellowish green 9.6GY 2.9/3.3 0.5% 30.6 in the centre
6 A67F23 light olive brown 2.0Y 5.3/7.5 0.2% 29.2 in the centre
7 3E682A dark yellowish green 8.4GY 4.0/6.6 0.4% 28.4 on the right
8 315A3E dark yellowish green 0.9G 3.5/4.4 0.5% 28.1 at the top right
9 55412E moderate olive brown 1.9Y 3.0/2.7 11% 27.1 in the centre
10 5B7227 moderate olive green 5.2GY 4.4/6.5 0.9% 25.3 at the top right
11 E78A1B strong orange 6.5YR 6.5/11.7 1.2% 21.7 on the right
12 2D2F22 dark grayish olive 0.6GY 1.7/0.9 0.5% 21.7 at the bottom right
13 506325 moderate olive green 4.4GY 3.9/5.4 0.1% 20.1 in the centre
14 D5B57A grayish yellow 1.4Y 7.4/4.9 0.2% 19.5 in the centre
15 A6781E light olive brown 2.2Y 5.3/7.9 2.1% 16.1 on the right
16 A55E2A brownish orange 4.0YR 4.6/7.9 12% 15.3 at the bottom left
17 DB8753 moderate orange 2.6YR 6.3/8.9 6.1% 14.5 at the top right
18 D4B576 moderate yellow 2.1Y 7.4/5.4 3.6% 14.3 on the left
19 B69A75 dark grayish yellow 1.5Y 6.4/3.6 1.6% 12.6 at the bottom right
20 A97419 strong yellowish brown 9.2YR 5.2/8.6 0.9% 11.3 at the top right
21 AF8D5F light yellowish brown 0.7Y 5.9/4.6 2.7% 10.9 at the top right
22 B69662 light yellowish brown 0.7Y 6.2/4.6 6.7% 10.9 at the top
23 CD891D deep orange yellow 9.3YR 6.2/10.0 31% 10.5 on the left

Colour name families

Family Area
orange yellow 31%
brown 20%
orange 18%
yellow 8.7%
black 5.6%
olive brown 4.3%
olive black 4.2%
yellow brown 2.6%
olive 1.7%
green 1.5%
olive green 1.0%

B) Texture Analysis

Metric Value
Global Roughness 0.181
Mean Local Roughness 0.006
Roughness Uniformity 0.015
Edge Density 0.006
Mean Gradient Magnitude 0.041
Gradient Variance 0.018
Gradient Smoothness 0.0
Directional Coherence 0.358
Pattern Complexity 0.094
Pattern Repetition 1.0
Detail Frequency Ratio 0.629
Spatial Variation 0.135
Texture Consistency 0.349

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.461
Brightness Variance 0.181
Brightness Uniformity 0.608
Brightness Skewness -0.816
Brightness Entropy 6.679
Rms Contrast 0.181
Michelson Contrast 1.0
Weber Contrast 0.804
Mean Local Contrast 0.006
Contrast Uniformity 0.0
Dynamic Range 0.969
Effective Dynamic Range 0.561
Shadow Percentage 22.389
Midtone Percentage 72.513
Highlight Percentage 5.098
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.004
Medium Contrast 0.008
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.041
Contrast Clustering 0.651

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.758
Color Clustering 0.573
Color Transition Smoothness 0.882
Transition Uniformity 0.874
Sharp Transition Ratio 0.1
Transition Directionality 0.343
Mean Saturation 0.615
Saturation Variance 0.054
Low Saturation Ratio 0.089
Medium Saturation Ratio 0.451
High Saturation Ratio 0.461
Saturation Clustering 1.0
Hue Concentration 0.972
Complementary Balance 0.0
Analogous Dominance 0.977
Temperature Bias 0.955

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). D Major - Research on Harmony - Variation 4 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0699.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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