AQC0846

Nanopublication — Computational Image Analysis - AQC0846

Claim 1: Computational Image Analysis - AQC0846

Analysis record [3]: Ab Major [1] - Research on Harmony - Variation 11 (AQC0846) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 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]: 2259x3012 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D9DDDB 16.4 white gainsboro
2 D18AB1 15.5 red-violet rosybrown
3 DCA0C3 14.3 red-violet plum
4 D8D2C7 12.7 yellow-orange lightgray
5 BD7AA2 9.7 red-violet palevioletred
6 CA6C44 9.6 orange peru
7 BB4F1E 8.2 orange burnt sienna
8 B595B8 6.6 red-violet steel gray
9 312225 5.1 red very dark gray
10 54444A 2.0 red dusty mauve
11 EBA48E 0.3 red-orange darksalmon [Accent]
12 8E7AA5 0.3 violet dusty mauve [Accent]

Color Families:

Family %
red-violet 46.1
orange 17.8
white 16.4
yellow-orange 12.7
red 7.1
red-orange 0.3
violet 0.3

Accent Colors:

Hex Family Name Chroma
EBA48E red-orange darksalmon 32.6
8E7AA5 violet dusty mauve 25.6

Texture Analysis

Metric Value
Global Roughness 0.187
Mean Local Roughness 0.011
Roughness Uniformity 0.013
Edge Density 0.029
Mean Gradient Magnitude 0.104
Gradient Variance 0.026
Gradient Smoothness 0.0
Directional Coherence 0.023
Pattern Complexity 0.113
Pattern Repetition 1.0
Detail Frequency Ratio 0.595
Spatial Variation 0.107
Texture Consistency 0.443

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.645
Brightness Variance 0.187
Brightness Uniformity 0.71
Brightness Skewness -0.896
Brightness Entropy 7.194
Rms Contrast 0.187
Michelson Contrast 1.0
Weber Contrast 0.525
Mean Local Contrast 0.013
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.655
Shadow Percentage 6.85
Midtone Percentage 44.188
Highlight Percentage 48.963
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.016
Coarse Contrast 0.029
Multiscale Contrast Ratio 0.203
Edge Contrast 0.104
Contrast Clustering 0.557

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.76
Color Clustering 0.613
Color Transition Smoothness 0.734
Transition Uniformity 0.822
Sharp Transition Ratio 0.1
Transition Directionality 0.03
Mean Saturation 0.309
Saturation Variance 0.059
Low Saturation Ratio 0.515
Medium Saturation Ratio 0.367
High Saturation Ratio 0.118
Saturation Clustering 1.0
Hue Concentration 0.895
Complementary Balance 0.0
Analogous Dominance 0.924
Temperature Bias 0.957

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 (2025). Ab Major - Research on Harmony - Variation 11 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0846.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/ab-major-research-on-harmony-variation-11_9d8.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)

1cc1139fe83a9f6dce080ee6ba537cf544800511b7615201342ef579527f2bfa