AQC0816

Nanopublication — Computational Image Analysis - AQC0816

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

Claim 1: Computational Image Analysis - AQC0816

Analysis record [3]: C Major [1] - Research on Harmony - Variation 10 (AQC0816) [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]: 2482x3309 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E1A787 27.6 orange burlywood
2 ECB597 18.0 orange tan
3 E4926B 12.1 orange darksalmon
4 DB805C 12.1 orange peru
5 CE9575 11.4 orange rosybrown
6 BC7E5B 7.0 orange indianred
7 D4634E 5.8 red-orange tomato
8 3C2016 2.9 red-orange very dark red
9 8D5940 1.8 orange burnt sienna
10 C7520E 1.2 orange chocolate
11 ADA394 0.3 yellow-orange steel gray [Accent]

Color Families:

Family %
orange 91.2
red-orange 8.8
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
ADA394 yellow-orange steel gray 9.1

Texture Analysis

Metric Value
Global Roughness 0.123
Mean Local Roughness 0.013
Roughness Uniformity 0.015
Edge Density 0.044
Mean Gradient Magnitude 0.12
Gradient Variance 0.033
Gradient Smoothness 0.0
Directional Coherence 0.017
Pattern Complexity 0.116
Pattern Repetition 1.0
Detail Frequency Ratio 0.598
Spatial Variation 0.059
Texture Consistency 0.652

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.644
Brightness Variance 0.123
Brightness Uniformity 0.809
Brightness Skewness -2.057
Brightness Entropy 6.607
Rms Contrast 0.123
Michelson Contrast 1.0
Weber Contrast 0.311
Mean Local Contrast 0.015
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.333
Shadow Percentage 3.223
Midtone Percentage 45.302
Highlight Percentage 51.475
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.006
Medium Contrast 0.019
Coarse Contrast 0.033
Multiscale Contrast Ratio 0.191
Edge Contrast 0.12
Contrast Clustering 0.348

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.703
Color Clustering 0.341
Color Transition Smoothness 0.699
Transition Uniformity 0.781
Sharp Transition Ratio 0.1
Transition Directionality 0.028
Mean Saturation 0.47
Saturation Variance 0.014
Low Saturation Ratio 0.012
Medium Saturation Ratio 0.961
High Saturation Ratio 0.027
Saturation Clustering 1.0
Hue Concentration 0.997
Complementary Balance 0.0
Analogous Dominance 1.0
Temperature Bias 1.0

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 Major - Research on Harmony - Variation 10 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0816.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/c-major-research-on-harmony-variation-10_91k.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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