AQC0821

Nanopublication — Computational Image Analysis - AQC0821

by Arnaud Quercy · C Minor - Research on Harmony - Variation 10 · 2025

Claim 1: Computational Image Analysis - AQC0821

Analysis record [3]: C Minor [1] - Research on Harmony - Variation 10 (AQC0821) [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]: 2274x3065 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E7B399 23.3 orange burlywood
2 E0A689 17.6 orange tan
3 D99777 17.3 orange darksalmon
4 EFC0A8 13.2 orange lightpink
5 CC8565 8.4 orange peru
6 997660 7.0 orange gray
7 B28F77 6.3 orange rosybrown
8 7C5A49 4.3 orange dimgray
9 412922 1.4 red-orange darkslategray
10 D36C1E 1.1 orange chocolate
11 704C70 0.3 red-violet dusty mauve [Accent]

Color Families:

Family %
orange 98.6
red-orange 1.4
red-violet 0.3

Accent Colors:

Hex Family Name Chroma
704C70 red-violet dusty mauve 26.6

Texture Analysis

Metric Value
Global Roughness 0.122
Mean Local Roughness 0.015
Roughness Uniformity 0.015
Edge Density 0.069
Mean Gradient Magnitude 0.137
Gradient Variance 0.03
Gradient Smoothness 0.0
Directional Coherence 0.014
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.615
Spatial Variation 0.084
Texture Consistency 0.611

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.667
Brightness Variance 0.122
Brightness Uniformity 0.817
Brightness Skewness -1.478
Brightness Entropy 6.706
Rms Contrast 0.122
Michelson Contrast 1.0
Weber Contrast 0.36
Mean Local Contrast 0.017
Contrast Uniformity 0.071
Dynamic Range 0.976
Effective Dynamic Range 0.38
Shadow Percentage 1.921
Midtone Percentage 37.361
Highlight Percentage 60.718
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.021
Coarse Contrast 0.036
Multiscale Contrast Ratio 0.22
Edge Contrast 0.137
Contrast Clustering 0.389

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.752
Color Clustering 0.476
Color Transition Smoothness 0.659
Transition Uniformity 0.802
Sharp Transition Ratio 0.1
Transition Directionality 0.02
Mean Saturation 0.389
Saturation Variance 0.008
Low Saturation Ratio 0.111
Medium Saturation Ratio 0.876
High Saturation Ratio 0.013
Saturation Clustering 1.0
Hue Concentration 0.995
Complementary Balance 0.0
Analogous Dominance 0.997
Temperature Bias 0.998

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). C Minor - Research on Harmony - Variation 10 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0821.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/c-minor-research-on-harmony-variation-10_93i.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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