AQC0735 | NAN-COL000219

Nanopublication — Computational Image Analysis - AQC0735

F Major - Research on Harmony - Variation 2

Claim 1: Computational Image Analysis - AQC0735

Computational analysis of the photograph of the artwork F Major - Research on Harmony - Variation 2 (AQC0735) [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 25 flat areas. The largest are dark blue (17%), moderate red (15%) and vivid red (11%). Among the others, those that stand out most sharply from their surroundings are bluish black at the bottom right (7.0%), very pale blue at the bottom (3.4%) and pale yellow on the left (0.8%). By colour name family: red 30%, blue 18%, yellow 12%, pink 7.8%, orange yellow 7.2%, purple 6.7%, black 6.2%, gray 4.9% and brown 4.3%.

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: 3024x4032 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 (3).

Rank Colour ISCC-NBS name Munsell Area Contrast Position
1 0B0A12 bluish black 7.8PB 0.3/0.6 7.0% 66.4 at the bottom right
2 BEC7C8 very pale blue 2.9PB 7.8/1.6 3.4% 45.0 at the bottom
3 B31C36 vivid red 4.9R 3.9/13.1 11% 41.8 at the bottom
4 E0D2B6 pale yellow 2.0Y 8.5/2.4 0.8% 40.7 on the left
5 BEA865 moderate yellow 6.1Y 6.9/5.3 0.6% 37.8 on the left
6 BAC4C4 light greenish gray 9.7BG 7.8/0.6 2.5% 36.6 at the bottom right
7 CBB490 light grayish yellowish brown 9.9YR 7.4/3.0 1.0% 35.8 at the bottom left
8 2D3445 dark blue 4.9PB 2.1/2.3 17% 33.8 on the left
9 EBCDC8 light pink 2.2R 8.4/3.1 2.1% 32.7 at the bottom left
10 EBC7E3 very light purple 8.9P 8.3/5.6 9.6% 27.2 at the top right
11 D93D3F vivid red 6.4R 4.9/14.5 0.4% 25.9 at the bottom left
12 9E4F56 moderate red 2.8R 4.2/7.3 3.0% 25.3 on the left
13 E0C4A4 pale orange yellow 7.7YR 8.1/3.5 4.8% 24.9 at the top right
14 AA3F45 moderate red 4.4R 4.1/10.3 15% 23.8 at the top
15 8C413A grayish red 7.8R 3.7/6.5 1.2% 23.4 in the centre
16 7E7C4B light olive 0.7GY 5.0/3.7 0.1% 23.1 at the bottom right
17 BA7C4B moderate orange 5.1YR 5.7/6.9 0.5% 23.0 at the bottom left
18 E7C8ED very pale purple 6.2P 8.5/4.8 0.2% 19.0 at the bottom
19 98714A moderate yellowish brown 8.1YR 5.1/4.8 3.0% 18.0 in the centre
20 CFA23E strong yellow 2.9Y 6.8/8.3 8.7% 15.6 in the centre
21 E2C293 pale orange yellow 0.2Y 8.0/4.4 1.2% 14.1 on the right
22 D07948 moderate orange 2.6YR 6.0/9.0 0.2% 9.1 at the bottom
23 D9C3A0 pale orange yellow 9.7YR 8.0/3.0 5.6% 8.2 on the right
24 C88F47 dark orange yellow 7.6YR 6.2/8.1 0.2% 6.8 at the bottom
25 BDC9C7 light greenish gray 6.9G 8.0/1.1 0.1% 1.7 at the bottom right

Colour name families

Family Area
red 30%
blue 18%
yellow 12%
pink 7.8%
orange yellow 7.2%
purple 6.7%
black 6.2%
gray 4.9%
brown 4.3%
orange 0.9%
green 0.5%

B) Texture Analysis

Metric Value
Global Roughness 0.261
Mean Local Roughness 0.026
Roughness Uniformity 0.026
Edge Density 0.113
Mean Gradient Magnitude 0.192
Gradient Variance 0.073
Gradient Smoothness 0.0
Directional Coherence 0.012
Pattern Complexity 0.123
Pattern Repetition 1.0
Detail Frequency Ratio 0.646
Spatial Variation 0.179
Texture Consistency 0.534

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.477
Brightness Variance 0.261
Brightness Uniformity 0.453
Brightness Skewness 0.037
Brightness Entropy 7.596
Rms Contrast 0.261
Michelson Contrast 1.0
Weber Contrast 0.825
Mean Local Contrast 0.027
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.788
Shadow Percentage 34.855
Midtone Percentage 31.612
Highlight Percentage 33.533
Shadow Clipping 0.032
Highlight Clipping 0.002
Tonal Balance 0.267
Fine Contrast 0.015
Medium Contrast 0.034
Coarse Contrast 0.045
Multiscale Contrast Ratio 0.33
Edge Contrast 0.192
Contrast Clustering 0.466

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.736
Color Clustering 0.757
Color Transition Smoothness 0.513
Transition Uniformity 0.494
Sharp Transition Ratio 0.1
Transition Directionality 0.015
Mean Saturation 0.46
Saturation Variance 0.059
Low Saturation Ratio 0.309
Medium Saturation Ratio 0.516
High Saturation Ratio 0.176
Saturation Clustering 0.998
Hue Concentration 0.47
Complementary Balance 0.201
Analogous Dominance 0.712
Temperature Bias 0.486

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). F Major - Research on Harmony - Variation 2 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0735.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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