AQC0853

Nanopublication — Computational Image Analysis - AQC0853

Claim 1: Computational Image Analysis - AQC0853

Analysis record [3]: D Major [1] - Research on Harmony - Variation 13 (AQC0853) [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]: 2226x2968 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 E2C5A5 18.2 yellow-orange burlywood
2 DDBA8F 16.9 yellow-orange tan
3 D7DCDB 15.8 white gainsboro
4 D0CDC4 14.0 yellow-orange lightgray
5 C8BCA8 10.5 yellow-orange silver
6 BBA78C 7.3 yellow-orange rosybrown
7 508482 6.2 green blue gray
8 729C8C 4.8 green lightslategray
9 323737 3.7 gray darkslategray
10 AB8864 2.6 orange peru
11 7F5E70 0.3 red-violet dusty mauve [Accent]
12 396A55 0.3 yellow-green darkslategray [Accent]
13 5A98AE 0.3 blue cadetblue [Accent]

Color Families:

Family %
yellow-orange 66.9
white 15.8
green 11.1
gray 3.7
orange 2.6
red-violet 0.3
yellow-green 0.3
blue 0.3

Accent Colors:

Hex Family Name Chroma
7F5E70 red-violet dusty mauve 17.7
396A55 yellow-green darkslategray 23.1
5A98AE blue cadetblue 22.8

Texture Analysis

Metric Value
Global Roughness 0.148
Mean Local Roughness 0.013
Roughness Uniformity 0.015
Edge Density 0.041
Mean Gradient Magnitude 0.113
Gradient Variance 0.028
Gradient Smoothness 0.0
Directional Coherence 0.013
Pattern Complexity 0.115
Pattern Repetition 1.0
Detail Frequency Ratio 0.599
Spatial Variation 0.079
Texture Consistency 0.632

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.725
Brightness Variance 0.148
Brightness Uniformity 0.795
Brightness Skewness -1.947
Brightness Entropy 6.63
Rms Contrast 0.148
Michelson Contrast 1.0
Weber Contrast 0.41
Mean Local Contrast 0.014
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.435
Shadow Percentage 3.594
Midtone Percentage 16.783
Highlight Percentage 79.622
Shadow Clipping 0.0
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.007
Medium Contrast 0.018
Coarse Contrast 0.031
Multiscale Contrast Ratio 0.218
Edge Contrast 0.113
Contrast Clustering 0.368

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.747
Color Clustering 0.672
Color Transition Smoothness 0.716
Transition Uniformity 0.814
Sharp Transition Ratio 0.1
Transition Directionality 0.014
Mean Saturation 0.218
Saturation Variance 0.019
Low Saturation Ratio 0.68
Medium Saturation Ratio 0.319
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.675
Complementary Balance 0.013
Analogous Dominance 0.799
Temperature Bias 0.599

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). D Major - Research on Harmony - Variation 13 — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0853.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2025/01/d-major-research-on-harmony-variation-13_9fy.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)

20ddf5ed8dad6dc7360f51ca7dc5e882894cea417696f58dab878755285ef411