AQC0850

Nanopublication — Computational Image Analysis - AQC0850

by Arnaud Quercy · Bb Minor - Research on Harmony - Variation 11 · 2025

Claim 1: Computational Image Analysis - AQC0850

Analysis record [3]: Bb Minor [1] - Research on Harmony - Variation 11 (AQC0850) [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]: 2288x3051 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E3DDD3 15.1 yellow-orange gainsboro
2 C7CCC3 13.9 yellow-green silver
3 AF91E4 13.8 violet mediumpurple
4 C14B94 11.7 red-violet palevioletred
5 906BCF 10.9 violet mediumslateblue
6 A52474 10.1 red mediumvioletred
7 6945AF 7.5 violet slateblue
8 AFB6AE 7.0 yellow-green steel gray
9 36157E 6.2 violet very dark purple
10 352A3B 3.8 violet very dark gray
11 C9987D 0.3 orange rosybrown [Accent]

Color Families:

Family %
violet 42.2
yellow-green 20.8
yellow-orange 15.1
red-violet 11.7
red 10.1
orange 0.3

Accent Colors:

Hex Family Name Chroma
C9987D orange rosybrown 25.8

Texture Analysis

Metric Value
Global Roughness 0.226
Mean Local Roughness 0.016
Roughness Uniformity 0.016
Edge Density 0.064
Mean Gradient Magnitude 0.139
Gradient Variance 0.03
Gradient Smoothness 0.0
Directional Coherence 0.008
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.607
Spatial Variation 0.164
Texture Consistency 0.532

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.568
Brightness Variance 0.226
Brightness Uniformity 0.602
Brightness Skewness -0.253
Brightness Entropy 7.677
Rms Contrast 0.226
Michelson Contrast 1.0
Weber Contrast 0.708
Mean Local Contrast 0.017
Contrast Uniformity 0.099
Dynamic Range 1.0
Effective Dynamic Range 0.706
Shadow Percentage 16.478
Midtone Percentage 44.465
Highlight Percentage 39.057
Shadow Clipping 0.0
Highlight Clipping 0.001
Tonal Balance 0.4
Fine Contrast 0.008
Medium Contrast 0.022
Coarse Contrast 0.036
Multiscale Contrast Ratio 0.227
Edge Contrast 0.139
Contrast Clustering 0.468

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.727
Color Clustering 0.6
Color Transition Smoothness 0.655
Transition Uniformity 0.804
Sharp Transition Ratio 0.1
Transition Directionality 0.011
Mean Saturation 0.39
Saturation Variance 0.082
Low Saturation Ratio 0.39
Medium Saturation Ratio 0.437
High Saturation Ratio 0.172
Saturation Clustering 1.0
Hue Concentration 0.855
Complementary Balance 0.0
Analogous Dominance 0.981
Temperature Bias 0.361

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). Bb Minor - Research on Harmony - Variation 11 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0850.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/bb-minor-research-on-harmony-variation-11_9es.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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