AQC0377

Nanopublication — Computational Image Analysis - AQC0377

by Arnaud Quercy · The traveler · 2022

Claim 1: Computational Image Analysis - AQC0377

Analysis record [3]: The [1] traveler (AQC0377) [2] by Arnaud Quercy [2]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2025-12-13.

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]: 1024x1024 pixels. Analysis date: 2025-12-13.

Color Analysis

Rank Color Hex % Family Name
1 755345 19.1 orange dimgray
2 64493E 17.4 orange dark brown
3 42312A 15.0 orange darkslategray
4 533E35 14.6 orange dark brown
5 86614E 12.4 orange dimgrey
6 2E241F 7.0 orange very dark gray
7 9F7457 5.9 orange indianred
8 020101 4.5 black black
9 B38B67 3.5 orange rosybrown
10 E4DCD5 0.6 white gainsboro
11 FFFCF0 0.3 yellow white [Accent]
12 FDF8EC 0.3 yellow-orange white [Accent]

Color Families:

Family %
orange 95.0
black 4.5
white 0.6
yellow 0.3
yellow-orange 0.3

Accent Colors:

Hex Family Name Chroma
FFFCF0 yellow white 6.1
FDF8EC yellow-orange white 6.0

Texture Analysis

Metric Value
Global Roughness 0.129
Mean Local Roughness 0.025
Roughness Uniformity 0.027
Edge Density 0.128
Mean Gradient Magnitude 0.192
Gradient Variance 0.071
Gradient Smoothness 0.0
Directional Coherence 0.031
Pattern Complexity 0.129
Pattern Repetition 1.0
Detail Frequency Ratio 0.66
Spatial Variation 0.048
Texture Consistency 0.779

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.311
Brightness Variance 0.129
Brightness Uniformity 0.585
Brightness Skewness 0.367
Brightness Entropy 6.811
Rms Contrast 0.129
Michelson Contrast 1.0
Weber Contrast 0.624
Mean Local Contrast 0.026
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.416
Shadow Percentage 55.933
Midtone Percentage 43.432
Highlight Percentage 0.636
Shadow Clipping 3.29
Highlight Clipping 0.001
Tonal Balance 0.0
Fine Contrast 0.014
Medium Contrast 0.033
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.192
Contrast Clustering 0.221

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.653
Color Clustering 0.755
Color Transition Smoothness 0.472
Transition Uniformity 0.526
Sharp Transition Ratio 0.1
Transition Directionality 0.032
Mean Saturation 0.38
Saturation Variance 0.015
Low Saturation Ratio 0.157
Medium Saturation Ratio 0.829
High Saturation Ratio 0.014
Saturation Clustering 0.996
Hue Concentration 0.988
Complementary Balance 0.002
Analogous Dominance 0.995
Temperature Bias 0.993

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 (2022). The traveler — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0377.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2022/08/the-traveler_4au.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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