AQC0687

Nanopublication — Computational Image Analysis - AQC0687

Claim 1: Computational Image Analysis - AQC0687

Analysis record [3]: C# Fourth [1] Interval - Reflexions 21 (AQC0687) [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]: 1920x2560 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D4D8D9 21.0 white lightgray
2 CBC9C2 19.2 white silver
3 B7B6AF 14.9 gray steel gray
4 9DA09F 10.8 gray steel gray
5 4A4E52 9.2 gray grayish purple
6 80868C 8.0 gray grayish purple
7 63666B 6.5 gray grayish purple
8 AEC3CB 6.0 blue lightsteelblue
9 6A99A8 3.3 blue cadetblue
10 2B2D30 1.1 gray very dark gray
11 896153 0.3 orange dimgray [Accent]
12 7DC2D3 0.3 blue-green skyblue [Accent]
13 916A60 0.3 red-orange dimgray [Accent]

Color Families:

Family %
gray 50.5
white 40.2
blue 9.3
orange 0.3
blue-green 0.3
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
896153 orange dimgray 20.5
7DC2D3 blue-green skyblue 22.7
916A60 red-orange dimgray 18.4

Texture Analysis

Metric Value
Global Roughness 0.181
Mean Local Roughness 0.019
Roughness Uniformity 0.02
Edge Density 0.087
Mean Gradient Magnitude 0.159
Gradient Variance 0.043
Gradient Smoothness 0.0
Directional Coherence 0.002
Pattern Complexity 0.121
Pattern Repetition 1.0
Detail Frequency Ratio 0.622
Spatial Variation 0.132
Texture Consistency 0.516

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.664
Brightness Variance 0.181
Brightness Uniformity 0.728
Brightness Skewness -0.933
Brightness Entropy 7.149
Rms Contrast 0.181
Michelson Contrast 1.0
Weber Contrast 0.581
Mean Local Contrast 0.021
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.565
Shadow Percentage 8.243
Midtone Percentage 30.041
Highlight Percentage 61.716
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.011
Medium Contrast 0.026
Coarse Contrast 0.04
Multiscale Contrast Ratio 0.266
Edge Contrast 0.159
Contrast Clustering 0.484

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.731
Color Clustering 0.902
Color Transition Smoothness 0.599
Transition Uniformity 0.706
Sharp Transition Ratio 0.1
Transition Directionality 0.003
Mean Saturation 0.091
Saturation Variance 0.007
Low Saturation Ratio 0.963
Medium Saturation Ratio 0.036
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.929
Complementary Balance 0.023
Analogous Dominance 0.976
Temperature Bias -0.941

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). C# Fourth Interval - Reflexions 21 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0687.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/c-fourth-interval-reflexions-21_7ne.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)

44b1879211a447a3a46e0a9b4d63fdbeb970caca33ba12f42de22fb5762dde5d