AQC0755 | NAN-COL000199

Nanopublication — Computational Image Analysis - AQC0755

D Minor - Research on Harmony - Variation 2

Claim 1: Computational Image Analysis - AQC0755

Computational analysis of the photograph of the artwork D Minor - Research on Harmony - Variation 2 (AQC0755) [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 26 flat areas. The largest are moderate orange yellow (16%), yellowish gray (15%) and strong orange yellow (15%). Among the others, those that stand out most sharply from their surroundings are black at the bottom right (9.4%), strong yellow at the bottom right (1.2%) and black in the centre (0.2%). By colour name family: orange 23%, gray 22%, orange yellow 17%, yellow 10%, black 9.4%, brown 9.2% and red 8.0%.

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: 2968x3958 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 (10).

Rank Colour ISCC-NBS name Munsell Area Contrast Position
1 1A1A1A black N 1.0/ 9.4% 47.2 at the bottom right
2 D1A435 strong yellow 2.0Y 6.9/9.2 1.2% 46.8 at the bottom right
3 272322 black N 1.4/ 0.2% 38.9 in the centre
4 E2C6A0 pale orange yellow 7.7YR 8.1/3.5 0.4% 38.4 at the bottom
5 452928 dark grayish reddish brown 7.6R 2.1/2.2 0.2% 35.0 in the centre
6 7A462A strong brown 2.7YR 3.5/5.6 2.7% 34.9 at the bottom
7 913C39 moderate red 5.7R 3.7/8.0 0.9% 31.4 on the right
8 A28132 dark yellow 3.2Y 5.6/6.6 0.6% 31.2 in the centre
9 913C53 moderate purplish red 9.6RP 3.8/8.1 1.8% 30.7 on the left
10 943C56 moderate purplish red 9.6RP 3.8/8.1 5.5% 29.0 on the right
11 B37349 brownish orange 4.0YR 5.4/6.6 3.1% 25.6 on the right
12 93433C dark reddish orange 7.6R 3.9/7.3 0.3% 24.3 on the left
13 B0AA9E yellowish gray 2.6Y 7.0/1.3 1.7% 21.4 at the bottom
14 B0A89A yellowish gray 2.6Y 7.0/1.3 5.4% 21.0 at the top left
15 B78439 dark orange yellow 9.9YR 5.7/7.1 1.9% 20.5 on the left
16 CA9D31 strong yellow 1.6Y 6.6/8.8 9.0% 19.3 at the bottom
17 EACBB1 light yellowish pink 5.5YR 8.4/3.0 0.6% 19.2 in the centre
18 B1ACA2 yellowish gray 8.9YR 7.0/0.8 15% 18.2 at the bottom left
19 DF992F strong orange yellow 9.6YR 6.8/10.1 15% 12.6 in the centre
20 DD802A strong orange 5.5YR 6.2/10.8 1.6% 9.9 at the top right
21 DC9952 moderate orange yellow 7.6YR 6.8/8.0 16% 9.5 at the top right
22 E87F12 strong orange 3.7YR 6.3/13.2 5.6% 7.7 at the top left
23 B17348 brownish orange 4.0YR 5.4/6.6 0.1% 4.3 on the right
24 C59F87 moderate yellowish pink 4.2YR 6.6/3.8 0.1% 1.6 on the left
25 E57E13 strong orange 4.3YR 6.1/12.7 0.2% 1.4 at the top
26 1A1916 olive black 0.6GY 1.0/0.9 0.3% 0.5 at the bottom right

Colour name families

Family Area
orange 23%
gray 22%
orange yellow 17%
yellow 10%
black 9.4%
brown 9.2%
red 8.0%
pink 0.8%

B) Texture Analysis

Metric Value
Global Roughness 0.194
Mean Local Roughness 0.017
Roughness Uniformity 0.015
Edge Density 0.081
Mean Gradient Magnitude 0.165
Gradient Variance 0.042
Gradient Smoothness 0.0
Directional Coherence 0.009
Pattern Complexity 0.12
Pattern Repetition 1.0
Detail Frequency Ratio 0.593
Spatial Variation 0.146
Texture Consistency 0.535

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.542
Brightness Variance 0.194
Brightness Uniformity 0.643
Brightness Skewness -1.289
Brightness Entropy 6.857
Rms Contrast 0.194
Michelson Contrast 1.0
Weber Contrast 0.799
Mean Local Contrast 0.021
Contrast Uniformity 0.092
Dynamic Range 1.0
Effective Dynamic Range 0.627
Shadow Percentage 17.097
Midtone Percentage 55.762
Highlight Percentage 27.14
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.026
Coarse Contrast 0.044
Multiscale Contrast Ratio 0.189
Edge Contrast 0.165
Contrast Clustering 0.465

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.767
Color Clustering 0.459
Color Transition Smoothness 0.584
Transition Uniformity 0.72
Sharp Transition Ratio 0.1
Transition Directionality 0.01
Mean Saturation 0.485
Saturation Variance 0.096
Low Saturation Ratio 0.324
Medium Saturation Ratio 0.396
High Saturation Ratio 0.28
Saturation Clustering 0.999
Hue Concentration 0.96
Complementary Balance 0.0
Analogous Dominance 0.993
Temperature Bias 0.999

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 Minor - Research on Harmony - Variation 2 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0755.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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