AQC0530

Nanopublication — Computational Image Analysis - AQC0530

by Arnaud Quercy · D Major9 - Research on Harmony - Variation 10 · 2024

Claim 1: Computational Image Analysis - AQC0530

Analysis record [3]: D Major9 - Research [1] on Harmony - Variation 10 (AQC0530) [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]: 2032x2709 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E7E5DF 27.3 white white
2 D9D5CE 15.9 white lightgray
3 BFA385 10.3 orange rosybrown
4 CBB7A3 9.5 orange tan
5 716F6D 8.0 gray dimgray
6 996848 7.0 orange burnt sienna
7 AD8868 6.6 orange ochre
8 92918E 5.7 gray gray
9 4A4747 5.2 gray darkslategray
10 B08337 4.5 yellow-orange peru
11 9CB2B6 0.3 blue-green steel gray [Accent]

Color Families:

Family %
white 43.2
orange 33.4
gray 18.9
yellow-orange 4.5
blue-green 0.3

Accent Colors:

Hex Family Name Chroma
9CB2B6 blue-green steel gray 8.6

Texture Analysis

Metric Value
Global Roughness 0.194
Mean Local Roughness 0.028
Roughness Uniformity 0.029
Edge Density 0.144
Mean Gradient Magnitude 0.216
Gradient Variance 0.083
Gradient Smoothness 0.0
Directional Coherence 0.013
Pattern Complexity 0.132
Pattern Repetition 1.0
Detail Frequency Ratio 0.668
Spatial Variation 0.106
Texture Consistency 0.746

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.693
Brightness Variance 0.194
Brightness Uniformity 0.72
Brightness Skewness -0.523
Brightness Entropy 7.083
Rms Contrast 0.194
Michelson Contrast 0.984
Weber Contrast 0.528
Mean Local Contrast 0.029
Contrast Uniformity 0.0
Dynamic Range 0.992
Effective Dynamic Range 0.565
Shadow Percentage 4.411
Midtone Percentage 37.97
Highlight Percentage 57.619
Shadow Clipping 0.0
Highlight Clipping 0.004
Tonal Balance 0.0
Fine Contrast 0.015
Medium Contrast 0.036
Coarse Contrast 0.047
Multiscale Contrast Ratio 0.319
Edge Contrast 0.216
Contrast Clustering 0.254

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.739
Color Clustering 0.835
Color Transition Smoothness 0.459
Transition Uniformity 0.478
Sharp Transition Ratio 0.1
Transition Directionality 0.017
Mean Saturation 0.172
Saturation Variance 0.04
Low Saturation Ratio 0.772
Medium Saturation Ratio 0.207
High Saturation Ratio 0.021
Saturation Clustering 1.0
Hue Concentration 0.992
Complementary Balance 0.0
Analogous Dominance 0.999
Temperature Bias 0.999

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 10 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0530.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/d-major9-research-on-harmony-variation-10_5yc.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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