AQC0923

Nanopublication — Computational Image Analysis - AQC0923

by Arnaud Quercy · C Major - Research on Harmony - Variations 16 · 2025

Claim 1: Computational Image Analysis - AQC0923

Analysis record [3]: C Major [1] - Research on Harmony - Variations 16 (AQC0923) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2025-12-11.

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]: 1802x2703 pixels. Analysis date: 2025-12-11.

Color Analysis

Rank Color Hex % Family Name
1 E99F5A 17.7 orange sandybrown
2 DF904C 17.4 orange peru
3 D84539 15.0 red-orange indianred
4 EA5F3E 14.8 red-orange tomato
5 E2B0B6 12.0 red lightpink
6 EA790C 11.7 orange darkorange
7 F0DFD3 4.5 orange antiquewhite
8 574842 3.7 orange dark brown
9 431B13 2.1 red-orange very dark red
10 ECDC4F 1.1 yellow khaki
11 F1D87B 0.3 yellow-orange khaki [Accent]

Color Families:

Family %
orange 55.0
red-orange 31.9
red 12.0
yellow 1.1
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
F1D87B yellow-orange khaki 49.1

Texture Analysis

Metric Value
Global Roughness 0.148
Mean Local Roughness 0.016
Roughness Uniformity 0.022
Edge Density 0.037
Mean Gradient Magnitude 0.128
Gradient Variance 0.054
Gradient Smoothness 0.0
Directional Coherence 0.049
Pattern Complexity 0.112
Pattern Repetition 1.0
Detail Frequency Ratio 0.627
Spatial Variation 0.058
Texture Consistency 0.586

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.593
Brightness Variance 0.148
Brightness Uniformity 0.75
Brightness Skewness -0.474
Brightness Entropy 7.079
Rms Contrast 0.148
Michelson Contrast 1.0
Weber Contrast 0.441
Mean Local Contrast 0.018
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.525
Shadow Percentage 5.507
Midtone Percentage 62.656
Highlight Percentage 31.836
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.022
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.128
Contrast Clustering 0.414

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.72
Color Clustering 0.331
Color Transition Smoothness 0.683
Transition Uniformity 0.638
Sharp Transition Ratio 0.1
Transition Directionality 0.06
Mean Saturation 0.616
Saturation Variance 0.057
Low Saturation Ratio 0.197
Medium Saturation Ratio 0.447
High Saturation Ratio 0.356
Saturation Clustering 0.999
Hue Concentration 0.97
Complementary Balance 0.0
Analogous Dominance 1.0
Temperature Bias 1.0

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). C Major - Research on Harmony - Variations 16 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0923.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/11/c-major-research-on-harmony-variations-16_iia.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 typecomputational analysis
Voicethird person
Epistemic statusempirical measurement
Methodologycomputational analysis
Certaintyhigh

Checksum (SHA-256)

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