AQC0554

Nanopublication — Computational Image Analysis - AQC0554

Claim 1: Computational Image Analysis - AQC0554

Computational image analysis [3] of artwork C Major9 - Research [1] on Harmony - Variation 6 (AQC0554) [2] by Arnaud Quercy [2] using k-means clustering method with 10 color extraction parameters. Analysis includes color distribution, texture metrics, brightness/contrast measurements, and spatial pattern characterization. Analysis completed on 2026-02-04.

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]: 2132x2843 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D6BA89 16.5 yellow-orange tan
2 292407 16.2 yellow very dark green
3 A97108 11.8 yellow-orange darkgoldenrod
4 C1826D 11.4 red-orange rosybrown
5 2D2937 10.4 violet very dark gray
6 3D371B 9.5 yellow darkslategray
7 916B28 8.7 yellow-orange burnt sienna
8 B5793F 8.2 orange peru
9 5B4D3E 4.8 orange dark brown
10 DACCC3 2.5 orange lightgray
11 816875 0.3 red-violet dusty mauve [Accent]
12 89686B 0.3 red dimgray [Accent]

Color Families:

Family %
yellow-orange 37.1
yellow 25.7
orange 15.4
red-orange 11.4
violet 10.4
red-violet 0.3
red 0.3

Accent Colors:

Hex Family Name Chroma
816875 red-violet dusty mauve 12.6
89686B red dimgray 14.3

Texture Analysis

Metric Value
Global Roughness 0.223
Mean Local Roughness 0.015
Roughness Uniformity 0.016
Edge Density 0.065
Mean Gradient Magnitude 0.125
Gradient Variance 0.032
Gradient Smoothness 0.0
Directional Coherence 0.056
Pattern Complexity 0.121
Pattern Repetition 1.0
Detail Frequency Ratio 0.623
Spatial Variation 0.177
Texture Consistency 0.68

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.419
Brightness Variance 0.223
Brightness Uniformity 0.467
Brightness Skewness 0.149
Brightness Entropy 7.208
Rms Contrast 0.223
Michelson Contrast 1.0
Weber Contrast 0.815
Mean Local Contrast 0.016
Contrast Uniformity 0.0
Dynamic Range 0.992
Effective Dynamic Range 0.639
Shadow Percentage 39.636
Midtone Percentage 41.317
Highlight Percentage 19.047
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.021
Coarse Contrast 0.033
Multiscale Contrast Ratio 0.23
Edge Contrast 0.125
Contrast Clustering 0.32

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.746
Color Clustering 0.696
Color Transition Smoothness 0.659
Transition Uniformity 0.789
Sharp Transition Ratio 0.1
Transition Directionality 0.068
Mean Saturation 0.571
Saturation Variance 0.067
Low Saturation Ratio 0.135
Medium Saturation Ratio 0.509
High Saturation Ratio 0.356
Saturation Clustering 0.999
Hue Concentration 0.808
Complementary Balance 0.026
Analogous Dominance 0.9
Temperature Bias 0.879

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). C Major9 - Research on Harmony - Variation 6 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0554.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-major9-research-on-harmony-variation-6_67o.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)

6879a2eb5ba7c2eb80f0fb287915fb3dc801ed6913e9e952ed0fd383268da38a