AQC0813

Nanopublication — Computational Image Analysis - AQC0813

Claim 1: Computational Image Analysis - AQC0813

Analysis record [3]: B Major [1] - Research on Harmony - Variation 6 (AQC0813) [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]: 2447x3262 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 ACC9AE 17.8 yellow-green silver
2 D1CEC2 16.9 yellow lightgray
3 99B897 15.1 yellow-green darkseagreen
4 AAC577 9.9 yellow-green ochre
5 89A275 9.7 yellow-green gray
6 E4DFD5 9.5 yellow-orange gainsboro
7 3C3F3B 6.8 gray darkslategray
8 222521 6.2 gray very dark gray
9 687A64 5.2 yellow-green dimgray
10 464172 2.7 violet dusty mauve
11 E0B19D 0.3 orange tan [Accent]
12 D0A69A 0.3 red-orange tan [Accent]

Color Families:

Family %
yellow-green 57.9
yellow 16.9
gray 13.0
yellow-orange 9.5
violet 2.7
orange 0.3
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
E0B19D orange tan 22.0
D0A69A red-orange tan 18.4

Texture Analysis

Metric Value
Global Roughness 0.214
Mean Local Roughness 0.022
Roughness Uniformity 0.019
Edge Density 0.124
Mean Gradient Magnitude 0.189
Gradient Variance 0.043
Gradient Smoothness 0.0
Directional Coherence 0.005
Pattern Complexity 0.115
Pattern Repetition 1.0
Detail Frequency Ratio 0.626
Spatial Variation 0.117
Texture Consistency 0.598

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.639
Brightness Variance 0.214
Brightness Uniformity 0.666
Brightness Skewness -1.144
Brightness Entropy 7.299
Rms Contrast 0.214
Michelson Contrast 1.0
Weber Contrast 0.72
Mean Local Contrast 0.025
Contrast Uniformity 0.219
Dynamic Range 1.0
Effective Dynamic Range 0.694
Shadow Percentage 15.005
Midtone Percentage 22.726
Highlight Percentage 62.27
Shadow Clipping 0.0
Highlight Clipping 0.024
Tonal Balance 0.0
Fine Contrast 0.012
Medium Contrast 0.03
Coarse Contrast 0.045
Multiscale Contrast Ratio 0.26
Edge Contrast 0.189
Contrast Clustering 0.402

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.73
Color Clustering 0.878
Color Transition Smoothness 0.53
Transition Uniformity 0.731
Sharp Transition Ratio 0.1
Transition Directionality 0.008
Mean Saturation 0.193
Saturation Variance 0.015
Low Saturation Ratio 0.826
Medium Saturation Ratio 0.173
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.747
Complementary Balance 0.052
Analogous Dominance 0.84
Temperature Bias -0.18

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). B Major - Research on Harmony - Variation 6 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0813.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/b-major-research-on-harmony-variation-6_90e.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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