AQC0722

Nanopublication — Computational Image Analysis - AQC0722

by Arnaud Quercy · Db Major - Research on Harmony - Variation 5 · 2024

Claim 1: Computational Image Analysis - AQC0722

Analysis record [3]: Db Major [1] - Research on Harmony - Variation 5 (AQC0722) [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]: 3024x4032 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 4F3632 17.6 red-orange darkslategray
2 905963 14.9 red dimgray
3 F45271 13.9 red-orange indianred
4 9BD3CD 13.1 green lightsteelblue
5 371E26 11.3 red very dark gray
6 6B444D 11.0 red dimgrey
7 DE3657 10.7 red-orange crimson
8 6FA2B5 4.2 blue cadetblue
9 E9C2A0 1.8 orange burlywood
10 565B8F 1.4 violet dusty mauve
11 12050C 0.3 red-violet black [Accent]

Color Families:

Family %
red-orange 42.3
red 37.2
green 13.1
blue 4.2
orange 1.8
violet 1.4
red-violet 0.3

Accent Colors:

Hex Family Name Chroma
12050C red-violet black 6.3

Texture Analysis

Metric Value
Global Roughness 0.192
Mean Local Roughness 0.026
Roughness Uniformity 0.024
Edge Density 0.144
Mean Gradient Magnitude 0.203
Gradient Variance 0.059
Gradient Smoothness 0.0
Directional Coherence 0.015
Pattern Complexity 0.124
Pattern Repetition 1.0
Detail Frequency Ratio 0.656
Spatial Variation 0.107
Texture Consistency 0.488

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.421
Brightness Variance 0.192
Brightness Uniformity 0.543
Brightness Skewness 0.458
Brightness Entropy 7.365
Rms Contrast 0.192
Michelson Contrast 1.0
Weber Contrast 0.75
Mean Local Contrast 0.028
Contrast Uniformity 0.121
Dynamic Range 1.0
Effective Dynamic Range 0.624
Shadow Percentage 35.94
Midtone Percentage 49.05
Highlight Percentage 15.01
Shadow Clipping 0.004
Highlight Clipping 0.001
Tonal Balance 0.134
Fine Contrast 0.015
Medium Contrast 0.034
Coarse Contrast 0.046
Multiscale Contrast Ratio 0.324
Edge Contrast 0.203
Contrast Clustering 0.512

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.751
Color Clustering 0.53
Color Transition Smoothness 0.488
Transition Uniformity 0.615
Sharp Transition Ratio 0.1
Transition Directionality 0.021
Mean Saturation 0.456
Saturation Variance 0.038
Low Saturation Ratio 0.259
Medium Saturation Ratio 0.593
High Saturation Ratio 0.148
Saturation Clustering 0.999
Hue Concentration 0.597
Complementary Balance 0.177
Analogous Dominance 0.79
Temperature Bias 0.6

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). Db Major - Research on Harmony - Variation 5 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0722.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/db-major-research-on-harmony-variation-5_810.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)

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