AQC0522

Nanopublication — Computational Image Analysis - AQC0522

by Arnaud Quercy · D Major9 - Research on Harmony - Variation 2 · 2024

Claim 1: Computational Image Analysis - AQC0522

Analysis record [3]: D Major9 - Research [1] on Harmony - Variation 2 (AQC0522) [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]: 1635x2179 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 CD986F 17.3 orange darksalmon
2 454542 13.8 gray darkslategray
3 DCAE8A 13.5 orange burlywood
4 BC8454 13.2 orange peru
5 A86C37 9.8 orange burnt sienna
6 666561 7.1 gray dimgray
7 834C23 7.1 orange russet
8 F0C9AC 6.9 orange wheat
9 242627 6.8 gray very dark gray
10 8D8C88 4.6 gray gray
11 BE9126 0.3 yellow-orange darkgoldenrod [Accent]

Color Families:

Family %
orange 67.8
gray 32.2
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
BE9126 yellow-orange darkgoldenrod 59.4

Texture Analysis

Metric Value
Global Roughness 0.195
Mean Local Roughness 0.041
Roughness Uniformity 0.025
Edge Density 0.249
Mean Gradient Magnitude 0.359
Gradient Variance 0.095
Gradient Smoothness 0.14
Directional Coherence 0.009
Pattern Complexity 0.134
Pattern Repetition 1.0
Detail Frequency Ratio 0.644
Spatial Variation 0.134
Texture Consistency 0.674

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.512
Brightness Variance 0.195
Brightness Uniformity 0.619
Brightness Skewness -0.239
Brightness Entropy 7.565
Rms Contrast 0.195
Michelson Contrast 1.0
Weber Contrast 0.67
Mean Local Contrast 0.047
Contrast Uniformity 0.43
Dynamic Range 1.0
Effective Dynamic Range 0.62
Shadow Percentage 22.947
Midtone Percentage 52.31
Highlight Percentage 24.743
Shadow Clipping 0.015
Highlight Clipping 0.02
Tonal Balance 0.286
Fine Contrast 0.022
Medium Contrast 0.058
Coarse Contrast 0.087
Multiscale Contrast Ratio 0.248
Edge Contrast 0.359
Contrast Clustering 0.326

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.719
Color Clustering 0.685
Color Transition Smoothness 0.092
Transition Uniformity 0.389
Sharp Transition Ratio 0.1
Transition Directionality 0.011
Mean Saturation 0.36
Saturation Variance 0.06
Low Saturation Ratio 0.365
Medium Saturation Ratio 0.558
High Saturation Ratio 0.077
Saturation Clustering 0.999
Hue Concentration 0.975
Complementary Balance 0.01
Analogous Dominance 0.989
Temperature Bias 0.978

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 (2024). D Major9 - Research on Harmony - Variation 2 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0522.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/d-major9-research-on-harmony-variation-2_5v8.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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