AQC0788

Nanopublication — Computational Image Analysis - AQC0788

by Arnaud Quercy · G Major - Research on Harmony - Variation 3 · 2024

Claim 1: Computational Image Analysis - AQC0788

Analysis record [3]: G Major [1] - Research on Harmony - Variation 3 (AQC0788) [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]: 2440x3661 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank	Hex	%	Family	Name
1	ADA592	26.4	yellow-orange	steel gray
2	1E1C1B	14.4	gray	very dark gray
3	C6BCAB	12.1	yellow-orange	silver
4	AC5A3B	12.0	orange	burnt sienna
5	934123	8.9	orange	russet
6	BD701D	7.9	orange	chocolate
7	A54D08	6.6	orange	russet
8	CD8646	6.1	orange	peru
9	A5A122	3.2	yellow	darkgoldenrod
10	C9C26A	2.3	yellow	ochre
11	430902	0.3	red-orange	very dark red [Accent]
12	DDE590	0.3	yellow-green	khaki [Accent]

Color Families:

Family	%
orange	41.5
yellow-orange	38.5
gray	14.4
yellow	5.5
red-orange	0.3
yellow-green	0.3

Accent Colors:

Hex	Family	Name	Chroma
430902	red-orange	very dark red	31.6
DDE590	yellow-green	khaki	43.7

Texture Analysis

Metric	Value
Global Roughness	0.204
Mean Local Roughness	0.012
Roughness Uniformity	0.01
Edge Density	0.056
Mean Gradient Magnitude	0.132
Gradient Variance	0.025
Gradient Smoothness	0.0
Directional Coherence	0.015
Pattern Complexity	0.114
Pattern Repetition	1.0
Detail Frequency Ratio	0.566
Spatial Variation	0.151
Texture Consistency	0.4

Brightness & Contrast Analysis

Metric	Value
Mean Brightness	0.496
Brightness Variance	0.204
Brightness Uniformity	0.589
Brightness Skewness	-0.63
Brightness Entropy	7.218
Rms Contrast	0.204
Michelson Contrast	1.0
Weber Contrast	0.837
Mean Local Contrast	0.016
Contrast Uniformity	0.13
Dynamic Range	1.0
Effective Dynamic Range	0.643
Shadow Percentage	18.726
Midtone Percentage	57.452
Highlight Percentage	23.821
Shadow Clipping	0.004
Highlight Clipping	0.003
Tonal Balance	0.0
Fine Contrast	0.005
Medium Contrast	0.019
Coarse Contrast	0.038
Multiscale Contrast Ratio	0.143
Edge Contrast	0.132
Contrast Clustering	0.6

Spatial Distribution Analysis

Metric	Value
Spatial Coherence	0.777
Color Clustering	0.51
Color Transition Smoothness	0.663
Transition Uniformity	0.837
Sharp Transition Ratio	0.1
Transition Directionality	0.023
Mean Saturation	0.426
Saturation Variance	0.11
Low Saturation Ratio	0.514
Medium Saturation Ratio	0.181
High Saturation Ratio	0.305
Saturation Clustering	1.0
Hue Concentration	0.97
Complementary Balance	0.0
Analogous Dominance	0.999
Temperature Bias	0.95

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). G Major - Research on Harmony - Variation 3 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0788.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/g-major-research-on-harmony-variation-3_8qo.html

[3] Quercy, A. (2025). Computational Image Analysis Standard - MMIDS-CMP-2025 https://multimodal.institute/en/publications/2025/11/mmids-cmp-2025-computational-image-analysis-standard-dg1.html

Epistemic profile

Claim type	computational analysis
Voice	third person
Epistemic status	empirical measurement
Methodology	computational analysis
Certainty	high

Checksum (SHA-256)

4b221edf53e6edcaa5864a3a04cd77e94c93b089e487b16e7a8d0b77e401ee54