AQC0802

Nanopublication — Computational Image Analysis - AQC0802

by Arnaud Quercy · Arches of Porto Venere · 2024

Claim 1: Computational Image Analysis - AQC0802

Analysis record [3]: Arches [1] of Porto Venere (AQC0802) [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]: 2359x3539 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 8D8D7C 15.0 yellow gray
2 9D9C8F 14.3 yellow steel gray
3 A9ADA6 14.0 gray steel gray
4 C7C7D3 12.8 violet lightgray
5 B5BBC2 10.7 gray silver
6 797B64 7.8 yellow-green dimgray
7 859BA2 7.2 blue lightslategray
8 535B58 6.8 gray dimgrey
9 5D8082 6.4 blue-green blue gray
10 343633 5.1 gray darkslategray

Color Families:

Family %
gray 36.5
yellow 29.3
violet 12.8
yellow-green 7.8
blue 7.2
blue-green 6.4

Texture Analysis

Metric Value
Global Roughness 0.15
Mean Local Roughness 0.018
Roughness Uniformity 0.015
Edge Density 0.083
Mean Gradient Magnitude 0.148
Gradient Variance 0.031
Gradient Smoothness 0.0
Directional Coherence 0.01
Pattern Complexity 0.119
Pattern Repetition 1.0
Detail Frequency Ratio 0.617
Spatial Variation 0.089
Texture Consistency 0.679

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.585
Brightness Variance 0.15
Brightness Uniformity 0.743
Brightness Skewness -0.746
Brightness Entropy 7.14
Rms Contrast 0.15
Michelson Contrast 1.0
Weber Contrast 0.51
Mean Local Contrast 0.019
Contrast Uniformity 0.231
Dynamic Range 0.961
Effective Dynamic Range 0.514
Shadow Percentage 7.464
Midtone Percentage 60.466
Highlight Percentage 32.07
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.01
Medium Contrast 0.024
Coarse Contrast 0.037
Multiscale Contrast Ratio 0.266
Edge Contrast 0.148
Contrast Clustering 0.321

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.709
Color Clustering 0.882
Color Transition Smoothness 0.621
Transition Uniformity 0.791
Sharp Transition Ratio 0.1
Transition Directionality 0.012
Mean Saturation 0.132
Saturation Variance 0.008
Low Saturation Ratio 0.934
Medium Saturation Ratio 0.066
High Saturation Ratio 0.0
Saturation Clustering 1.0
Hue Concentration 0.462
Complementary Balance 0.017
Analogous Dominance 0.531
Temperature Bias -0.433

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). Arches of Porto Venere — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0802.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2024/01/arches-of-porto-venere_8w4.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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