AQC0648

Nanopublication — Computational Image Analysis - AQC0648

Claim 1: Computational Image Analysis - AQC0648

Analysis record [3]: A minor - Research [1] on Harmony - Variation 1 (AQC0648) [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]: 2385x3577 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 C62A1D 22.8 red-orange firebrick
2 E99B24 22.4 orange goldenrod
3 E5C82B 16.5 yellow-orange gold
4 D04544 7.9 red-orange indianred
5 44301F 7.8 orange darkslategray
6 20150C 6.0 orange black
7 744320 5.9 orange russet
8 A4874B 4.1 yellow-orange peru
9 6D5E4F 3.8 orange dimgray
10 E1AE8C 2.7 orange burlywood
11 F7E565 0.3 yellow khaki [Accent]
12 E37D92 0.3 red palevioletred [Accent]
13 3D434D 0.3 blue-violet grayish purple [Accent]

Color Families:

Family %
orange 48.7
red-orange 30.7
yellow-orange 20.6
yellow 0.3
red 0.3
blue-violet 0.3

Accent Colors:

Hex Family Name Chroma
F7E565 yellow khaki 63.6
E37D92 red palevioletred 42.4
3D434D blue-violet grayish purple 7.0

Texture Analysis

Metric Value
Global Roughness 0.211
Mean Local Roughness 0.039
Roughness Uniformity 0.044
Edge Density 0.164
Mean Gradient Magnitude 0.307
Gradient Variance 0.176
Gradient Smoothness 0.0
Directional Coherence 0.015
Pattern Complexity 0.118
Pattern Repetition 1.0
Detail Frequency Ratio 0.668
Spatial Variation 0.129
Texture Consistency 0.646

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.478
Brightness Variance 0.211
Brightness Uniformity 0.559
Brightness Skewness -0.109
Brightness Entropy 7.429
Rms Contrast 0.211
Michelson Contrast 1.0
Weber Contrast 0.73
Mean Local Contrast 0.042
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.643
Shadow Percentage 25.742
Midtone Percentage 48.496
Highlight Percentage 25.762
Shadow Clipping 0.028
Highlight Clipping 0.004
Tonal Balance 0.081
Fine Contrast 0.022
Medium Contrast 0.052
Coarse Contrast 0.072
Multiscale Contrast Ratio 0.309
Edge Contrast 0.307
Contrast Clustering 0.354

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.732
Color Clustering 0.415
Color Transition Smoothness 0.215
Transition Uniformity 0.0
Sharp Transition Ratio 0.1
Transition Directionality 0.014
Mean Saturation 0.738
Saturation Variance 0.047
Low Saturation Ratio 0.078
Medium Saturation Ratio 0.176
High Saturation Ratio 0.746
Saturation Clustering 0.995
Hue Concentration 0.935
Complementary Balance 0.002
Analogous Dominance 0.995
Temperature Bias 0.994

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). A minor - Research on Harmony - Variation 1 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0648.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/a-minor-research-on-harmony-variation-1_788.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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