AQC1125

Nanopublication — Computational Image Analysis - AQC1125

C Octaves - Research on Harmony - Reflections 46

Claim 1: Computational Image Analysis - AQC1125

Analysis record: C Octaves - Research on Harmony - Reflections 46 (AQC1125) [1] by Arnaud Quercy [2], per IDS-CMP-2025 [3]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2026-10-02.

Context

Analysis performed according to IDS-CMP-2025 [3] includes four metric categories: (a) Color distribution via k-means (10 colors), (b) Texture analysis using Haralick features, (c) Brightness and contrast measurements, (d) Spatial pattern characterization. Source image: 3024x4032 pixels. Analysis date: 2026-10-02.

A) Color Analysis

Rank Color Hex % Family Name
1 8E8474 18.7 yellow-orange gray
2 9C9183 16.9 yellow-orange grey
3 AA9F90 16.3 yellow-orange rosybrown
4 B6AB9C 15.3 yellow-orange steel gray
5 7E715B 10.1 yellow-orange dimgray
6 821A07 7.1 red-orange maroon
7 86513B 5.6 orange burnt sienna
8 DAD6CB 3.7 yellow lightgray
9 635442 3.5 yellow-orange dark brown
10 0E0705 2.8 black black

Color Families:

Family %
yellow-orange 80.8
red-orange 7.1
orange 5.6
yellow 3.7
black 2.8

B) Texture Analysis

Metric Value
Global Roughness 0.164
Mean Local Roughness 0.022
Roughness Uniformity 0.011
Edge Density 0.081
Mean Gradient Magnitude 0.149
Gradient Variance 0.02
Gradient Smoothness 0.053
Directional Coherence 0.012
Pattern Complexity 0.136
Pattern Repetition 1.0
Detail Frequency Ratio 0.651
Spatial Variation 0.112
Texture Consistency 0.589

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.528
Brightness Variance 0.164
Brightness Uniformity 0.689
Brightness Skewness -0.951
Brightness Entropy 7.082
Rms Contrast 0.164
Michelson Contrast 1.0
Weber Contrast 0.598
Mean Local Contrast 0.022
Contrast Uniformity 0.415
Dynamic Range 0.996
Effective Dynamic Range 0.514
Shadow Percentage 11.96
Midtone Percentage 71.894
Highlight Percentage 16.146
Shadow Clipping 0.002
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.015
Medium Contrast 0.026
Coarse Contrast 0.033
Multiscale Contrast Ratio 0.456
Edge Contrast 0.149
Contrast Clustering 0.411

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.738
Color Clustering 0.716
Color Transition Smoothness 0.625
Transition Uniformity 0.865
Sharp Transition Ratio 0.1
Transition Directionality 0.012
Mean Saturation 0.265
Saturation Variance 0.053
Low Saturation Ratio 0.786
Medium Saturation Ratio 0.135
High Saturation Ratio 0.079
Saturation Clustering 0.999
Hue Concentration 0.971
Complementary Balance 0.0
Analogous Dominance 0.998
Temperature Bias 0.998

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 Ideamorphic Studies' computational imaging systems.

References

  1. [1] Quercy, A. (2026). C Octaves - Research on Harmony - Reflections 46 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC1125.html
  2. [2] Quercy, A. (2025). ORCID https://orcid.org/0009-0000-2662-7790
  3. [3] Quercy, A. (2026). Computational Image Analysis Standard. https://ideamorphism.org/en/measurements/2025/11/ids-cmp-2025-computational-image-analysis-standard-5dq9.html

Where this work lives

Epistemic profile

Claim typecomputational analysis
Voicethird person
Epistemic statusempirical measurement
Methodologycomputational analysis
Certaintyhigh

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