AQC0526

Nanopublication — Computational Image Analysis - AQC0526

by Arnaud Quercy · D Major9 - Research on Harmony - Variation 6 · 2024

Claim 1: Computational Image Analysis - AQC0526

Analysis record [3]: D Major9 - Research [1] on Harmony - Variation 6 (AQC0526) [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]: 1802x2402 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E3E3DE 38.0 white gainsboro
2 BA9854 9.3 yellow-orange peru
3 CAB89F 8.7 yellow-orange tan
4 95907C 8.3 yellow gray
5 74726E 7.8 gray dimgray
6 AFA28C 6.6 yellow-orange rosybrown
7 5B5752 5.9 gray dimgrey
8 CDCBC4 5.4 white silver
9 CCAB6F 5.2 yellow-orange ochre
10 A97E54 4.7 orange indianred

Color Families:

Family %
white 43.4
yellow-orange 29.9
gray 13.8
yellow 8.3
orange 4.7

Texture Analysis

Metric Value
Global Roughness 0.178
Mean Local Roughness 0.024
Roughness Uniformity 0.023
Edge Density 0.14
Mean Gradient Magnitude 0.189
Gradient Variance 0.058
Gradient Smoothness 0.0
Directional Coherence 0.017
Pattern Complexity 0.136
Pattern Repetition 1.0
Detail Frequency Ratio 0.659
Spatial Variation 0.066
Texture Consistency 0.724

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.707
Brightness Variance 0.178
Brightness Uniformity 0.748
Brightness Skewness -0.477
Brightness Entropy 6.905
Rms Contrast 0.178
Michelson Contrast 0.91
Weber Contrast 0.506
Mean Local Contrast 0.026
Contrast Uniformity 0.041
Dynamic Range 0.953
Effective Dynamic Range 0.529
Shadow Percentage 1.583
Midtone Percentage 40.751
Highlight Percentage 57.666
Shadow Clipping 0.0
Highlight Clipping 0.002
Tonal Balance 0.0
Fine Contrast 0.013
Medium Contrast 0.032
Coarse Contrast 0.043
Multiscale Contrast Ratio 0.308
Edge Contrast 0.189
Contrast Clustering 0.276

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.722
Color Clustering 0.774
Color Transition Smoothness 0.531
Transition Uniformity 0.64
Sharp Transition Ratio 0.1
Transition Directionality 0.022
Mean Saturation 0.167
Saturation Variance 0.037
Low Saturation Ratio 0.773
Medium Saturation Ratio 0.227
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.985
Complementary Balance 0.0
Analogous Dominance 0.999
Temperature Bias 0.961

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). D Major9 - Research on Harmony - Variation 6 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0526.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/d-major9-research-on-harmony-variation-6_5ws.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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