AQC0809

Nanopublication — Computational Image Analysis - AQC0809

Claim 1: Computational Image Analysis - AQC0809

Analysis record [3]: A Major [1] - Research on Harmony - Variation 6 (AQC0809) [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]: 2421x3228 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 D9D4C8 19.4 yellow-orange lightgray
2 D4C9B5 17.4 yellow-orange silver
3 DCDFDD 17.4 white gainsboro
4 A6A097 10.1 yellow-orange steel gray
5 C9BBA0 9.8 yellow-orange tan
6 8E877F 9.1 yellow-orange gray
7 716860 5.1 orange dimgray
8 22282A 4.2 gray very dark gray
9 D8CA4B 4.2 yellow ochre
10 579BB1 3.4 blue cadetblue
11 8EB8BD 0.3 blue-green steel gray [Accent]
12 83B7B4 0.3 green mediumaquamarine [Accent]

Color Families:

Family %
yellow-orange 65.8
white 17.4
orange 5.1
gray 4.2
yellow 4.2
blue 3.4
blue-green 0.3
green 0.3

Accent Colors:

Hex Family Name Chroma
8EB8BD blue-green steel gray 14.8
83B7B4 green mediumaquamarine 18.4

Texture Analysis

Metric Value
Global Roughness 0.178
Mean Local Roughness 0.016
Roughness Uniformity 0.02
Edge Density 0.066
Mean Gradient Magnitude 0.131
Gradient Variance 0.045
Gradient Smoothness 0.0
Directional Coherence 0.026
Pattern Complexity 0.118
Pattern Repetition 1.0
Detail Frequency Ratio 0.618
Spatial Variation 0.122
Texture Consistency 0.422

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.715
Brightness Variance 0.178
Brightness Uniformity 0.751
Brightness Skewness -1.57
Brightness Entropy 6.899
Rms Contrast 0.178
Michelson Contrast 1.0
Weber Contrast 0.443
Mean Local Contrast 0.017
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.514
Shadow Percentage 4.472
Midtone Percentage 25.497
Highlight Percentage 70.031
Shadow Clipping 0.006
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.021
Coarse Contrast 0.035
Multiscale Contrast Ratio 0.242
Edge Contrast 0.131
Contrast Clustering 0.578

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.753
Color Clustering 0.632
Color Transition Smoothness 0.668
Transition Uniformity 0.696
Sharp Transition Ratio 0.1
Transition Directionality 0.032
Mean Saturation 0.149
Saturation Variance 0.024
Low Saturation Ratio 0.896
Medium Saturation Ratio 0.093
High Saturation Ratio 0.012
Saturation Clustering 1.0
Hue Concentration 0.402
Complementary Balance 0.067
Analogous Dominance 0.674
Temperature Bias 0.334

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). A Major - Research on Harmony - Variation 6 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0809.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/a-major-research-on-harmony-variation-6_8yu.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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