AQC0694

Nanopublication — Computational Image Analysis - AQC0694

by Arnaud Quercy · Bb Major - Research on Harmony - Variation 2 · 2024

Claim 1: Computational Image Analysis - AQC0694

Analysis record [3]: Bb Major [1] - Research on Harmony - Variation 2 (AQC0694) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2026-02-03.

Context

Analysis performed according to MMIDS-CMP-2025 [3] includes four metric categories: (1) Color distribution via k-means (10 colors), (2) Texture analysis using Haralick features, (3) Brightness and contrast measurements, (4) Spatial pattern characterization. Source image [5]: 2693x3535 pixels. Analysis date: 2026-02-03.

Color Analysis

Rank Color Hex % Family Name
1 AE642C 21.9 orange burnt sienna
2 4A2D37 16.7 red dusty mauve
3 E1833F 15.3 orange peru
4 28211E 14.1 gray very dark gray
5 CF7C14 9.5 orange chocolate
6 D0AB74 6.8 yellow-orange ochre
7 673A39 5.7 red-orange dark brown
8 89504D 4.6 red-orange burnt sienna
9 B3756C 3.8 red-orange indianred
10 D5B79A 1.7 orange tan

Color Families:

Family %
orange 48.4
red 16.7
gray 14.1
red-orange 14.1
yellow-orange 6.8

Texture Analysis

Metric Value
Global Roughness 0.182
Mean Local Roughness 0.006
Roughness Uniformity 0.015
Edge Density 0.007
Mean Gradient Magnitude 0.046
Gradient Variance 0.018
Gradient Smoothness 0.0
Directional Coherence 0.249
Pattern Complexity 0.105
Pattern Repetition 1.0
Detail Frequency Ratio 0.63
Spatial Variation 0.149
Texture Consistency 0.434

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.412
Brightness Variance 0.182
Brightness Uniformity 0.559
Brightness Skewness -0.128
Brightness Entropy 6.822
Rms Contrast 0.182
Michelson Contrast 0.992
Weber Contrast 0.755
Mean Local Contrast 0.007
Contrast Uniformity 0.0
Dynamic Range 0.992
Effective Dynamic Range 0.561
Shadow Percentage 36.349
Midtone Percentage 55.787
Highlight Percentage 7.865
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.003
Medium Contrast 0.009
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.046
Contrast Clustering 0.566

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.789
Color Clustering 0.451
Color Transition Smoothness 0.871
Transition Uniformity 0.882
Sharp Transition Ratio 0.1
Transition Directionality 0.27
Mean Saturation 0.557
Saturation Variance 0.049
Low Saturation Ratio 0.121
Medium Saturation Ratio 0.451
High Saturation Ratio 0.428
Saturation Clustering 1.0
Hue Concentration 0.938
Complementary Balance 0.0
Analogous Dominance 0.997
Temperature Bias 1.0

Methodology

This analysis employs standardized computational methods for objective image characterization. Color extraction uses k-means clustering algorithm. Texture analysis applies Haralick feature extraction. Brightness metrics include mean, variance, and distribution analysis. Spatial patterns are characterized through coherence and clustering measurements. All methods are deterministic and reproducible. Analysis performed by Multimodal Institute's computational imaging systems.

References

[1] Arnaud Quercy (2024). Bb Major - Research on Harmony - Variation 2 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0694.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/bb-major-research-on-harmony-variation-2_7q4.html

[3] Quercy, A. (2025). Computational Image Analysis Standard - MMIDS-CMP-2025 https://multimodal.institute/en/publications/2025/10/mmids-cmp-2025-computational-image-analysis-standard-dg1.html

Epistemic profile

Claim typecomputational analysis
Voicethird person
Epistemic statusempirical measurement
Methodologycomputational analysis
Certaintyhigh

Checksum (SHA-256)

397977a4fca31327e35d92098db651a3f698be6603ab0559cb6b7f7bdca72095