AQC0966

Nanopublication — Computational Image Analysis - AQC0966

by Arnaud Quercy · Em7b5 - Research in harmony · 2026

Claim 1: Computational Image Analysis - AQC0966

Analysis record [3]: Em7b5 - Research [1] in harmony (AQC0966) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2026-03-05.

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]: 2046x2046 pixels. Analysis date: 2026-03-05.

Color Analysis

Rank Color Hex % Family Name
1 BFC0BD 20.5 gray silver
2 A5B6E3 16.2 blue-violet lightsteelblue
3 2A2E33 13.0 gray very dark gray
4 14161A 12.8 black black
5 8494AC 8.6 blue-violet lightslategray
6 DAE1E9 8.5 blue-violet gainsboro
7 464B51 6.3 gray grayish purple
8 4390D1 6.2 blue-violet steelblue
9 60708D 5.5 blue-violet grayish purple
10 C4D662 2.4 yellow-green ochre
11 DCCC9C 0.3 yellow-orange burlywood [Accent]
12 FDFBE7 0.3 yellow oldlace [Accent]

Color Families:

Family %
blue-violet 45.0
gray 39.8
black 12.8
yellow-green 2.4
yellow-orange 0.3
yellow 0.3

Accent Colors:

Hex Family Name Chroma
DCCC9C yellow-orange burlywood 26.1
FDFBE7 yellow oldlace 10.4

Texture Analysis

Metric Value
Global Roughness 0.274
Mean Local Roughness 0.045
Roughness Uniformity 0.036
Edge Density 0.218
Mean Gradient Magnitude 0.35
Gradient Variance 0.149
Gradient Smoothness 0.0
Directional Coherence 0.001
Pattern Complexity 0.121
Pattern Repetition 1.0
Detail Frequency Ratio 0.666
Spatial Variation 0.229
Texture Consistency 0.694

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.522
Brightness Variance 0.274
Brightness Uniformity 0.475
Brightness Skewness -0.389
Brightness Entropy 7.635
Rms Contrast 0.274
Michelson Contrast 1.0
Weber Contrast 0.864
Mean Local Contrast 0.05
Contrast Uniformity 0.197
Dynamic Range 1.0
Effective Dynamic Range 0.792
Shadow Percentage 30.894
Midtone Percentage 23.461
Highlight Percentage 45.644
Shadow Clipping 0.002
Highlight Clipping 0.008
Tonal Balance 0.253
Fine Contrast 0.024
Medium Contrast 0.06
Coarse Contrast 0.074
Multiscale Contrast Ratio 0.326
Edge Contrast 0.35
Contrast Clustering 0.306

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.782
Color Clustering 0.798
Color Transition Smoothness 0.097
Transition Uniformity 0.036
Sharp Transition Ratio 0.1
Transition Directionality 0.002
Mean Saturation 0.217
Saturation Variance 0.034
Low Saturation Ratio 0.763
Medium Saturation Ratio 0.207
High Saturation Ratio 0.031
Saturation Clustering 0.999
Hue Concentration 0.821
Complementary Balance 0.049
Analogous Dominance 0.911
Temperature Bias -0.862

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). Em7b5 - Research in harmony — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0966.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2026/03/em7b5-research-in-harmony_1yns.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)

e42807a4d92a48be04929b25b24281417cbb3ecd8bc5882d356c531e7fc3ce39