AQC0949

Nanopublication — Computational Image Analysis - AQC0949

by Arnaud Quercy · B Minor 7 - Research on Harmony · 2026

Claim 1: Computational Image Analysis - AQC0949

Analysis record [3]: B Minor [1] 7 - Research on Harmony (AQC0949) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2026-03-04.

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]: 1846x2769 pixels. Analysis date: 2026-03-04.

Color Analysis

Rank Color Hex % Family Name
1 A7AAAA 21.5 gray steel gray
2 BCC0C0 19.7 gray silver
3 E5E3D5 10.6 yellow gainsboro
4 232829 8.5 gray very dark gray
5 DCC58F 8.4 yellow-orange burlywood
6 3D4A46 7.7 green darkslategray
7 547C5B 7.6 yellow-green dimgray
8 7A8B7B 6.2 yellow-green gray
9 BCAF7D 6.1 yellow ochre
10 5B92B3 3.7 blue cadetblue
11 306EAB 0.3 blue-violet grayish purple [Accent]
12 997A58 0.3 orange gray [Accent]

Color Families:

Family %
gray 49.7
yellow 16.6
yellow-green 13.8
yellow-orange 8.4
green 7.7
blue 3.7
blue-violet 0.3
orange 0.3

Accent Colors:

Hex Family Name Chroma
306EAB blue-violet grayish purple 38.0
997A58 orange gray 24.0

Texture Analysis

Metric Value
Global Roughness 0.217
Mean Local Roughness 0.029
Roughness Uniformity 0.023
Edge Density 0.165
Mean Gradient Magnitude 0.24
Gradient Variance 0.075
Gradient Smoothness 0.0
Directional Coherence 0.021
Pattern Complexity 0.118
Pattern Repetition 1.0
Detail Frequency Ratio 0.632
Spatial Variation 0.104
Texture Consistency 0.733

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.61
Brightness Variance 0.217
Brightness Uniformity 0.644
Brightness Skewness -0.826
Brightness Entropy 7.503
Rms Contrast 0.217
Michelson Contrast 1.0
Weber Contrast 0.723
Mean Local Contrast 0.032
Contrast Uniformity 0.246
Dynamic Range 1.0
Effective Dynamic Range 0.722
Shadow Percentage 15.556
Midtone Percentage 29.658
Highlight Percentage 54.786
Shadow Clipping 0.0
Highlight Clipping 0.021
Tonal Balance 0.09
Fine Contrast 0.015
Medium Contrast 0.04
Coarse Contrast 0.058
Multiscale Contrast Ratio 0.261
Edge Contrast 0.24
Contrast Clustering 0.267

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.718
Color Clustering 0.823
Color Transition Smoothness 0.39
Transition Uniformity 0.495
Sharp Transition Ratio 0.1
Transition Directionality 0.02
Mean Saturation 0.159
Saturation Variance 0.024
Low Saturation Ratio 0.772
Medium Saturation Ratio 0.222
High Saturation Ratio 0.006
Saturation Clustering 0.999
Hue Concentration 0.456
Complementary Balance 0.099
Analogous Dominance 0.49
Temperature Bias -0.167

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 (2026). B Minor 7 - Research on Harmony — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0949.html

[2] Quercy, A. (2026). B Minor 7 - Research on Harmony - Gallery. https://artquamanima.com/en/artworks/2026/03/b-minor-7-research-on-harmony_1yfq.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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