AQC0774 | NAN-COL000180

Nanopublication — Computational Image Analysis - AQC0774

C Major - Research on Harmony - Variation 7

Claim 1: Computational Image Analysis - AQC0774

Analysis record: C Major - Research on Harmony - Variation 7 (AQC0774) [1] by Arnaud Quercy [2], per IDS-CMP-2025 [3]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2025-10-03.

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: 2454x3682 pixels. Analysis date: 2025-10-03.

A) Color Analysis

Rank Color Hex % Family Name
1 BCB3A9 19.3 yellow-orange steel gray
2 262328 15.2 gray very dark gray
3 9A3C36 14.0 red-orange brown
4 C9443E 13.1 red-orange indianred
5 CEC0B8 9.7 orange silver
6 39373E 8.8 gray dusty mauve
7 A9A196 7.7 yellow-orange steel gray
8 C08B56 6.0 orange peru
9 E7780B 3.5 orange chocolate
10 585759 2.7 gray dusty mauve
11 160208 0.3 red black [Accent]
12 81763E 0.3 yellow olivedrab [Accent]

Color Families:

Family %
red-orange 27.2
yellow-orange 27.0
gray 26.6
orange 19.2
red 0.3
yellow 0.3

Accent Colors:

Hex Family Name Chroma
160208 red black 8.1
81763E yellow olivedrab 32.2

B) Texture Analysis

Metric Value
Global Roughness 0.22
Mean Local Roughness 0.011
Roughness Uniformity 0.011
Edge Density 0.041
Mean Gradient Magnitude 0.121
Gradient Variance 0.028
Gradient Smoothness 0.0
Directional Coherence 0.024
Pattern Complexity 0.117
Pattern Repetition 1.0
Detail Frequency Ratio 0.567
Spatial Variation 0.154
Texture Consistency 0.592

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.471
Brightness Variance 0.22
Brightness Uniformity 0.533
Brightness Skewness -0.118
Brightness Entropy 7.316
Rms Contrast 0.22
Michelson Contrast 1.0
Weber Contrast 0.788
Mean Local Contrast 0.014
Contrast Uniformity 0.0
Dynamic Range 1.0
Effective Dynamic Range 0.62
Shadow Percentage 28.969
Midtone Percentage 40.319
Highlight Percentage 30.712
Shadow Clipping 0.001
Highlight Clipping 0.0
Tonal Balance 0.043
Fine Contrast 0.005
Medium Contrast 0.018
Coarse Contrast 0.036
Multiscale Contrast Ratio 0.146
Edge Contrast 0.121
Contrast Clustering 0.408

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.764
Color Clustering 0.497
Color Transition Smoothness 0.676
Transition Uniformity 0.795
Sharp Transition Ratio 0.1
Transition Directionality 0.035
Mean Saturation 0.342
Saturation Variance 0.083
Low Saturation Ratio 0.602
Medium Saturation Ratio 0.256
High Saturation Ratio 0.142
Saturation Clustering 1.0
Hue Concentration 0.815
Complementary Balance 0.024
Analogous Dominance 0.903
Temperature Bias 0.829

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. (2024). C Major - Research on Harmony - Variation 7 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0774.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/2025/09/ids-cmp-2025-computational-image-analysis-standard-5dq9.html

Epistemic profile

Claim typecomputational analysis
Voicethird person
Epistemic statusempirical measurement
Methodologycomputational analysis
Certaintyhigh

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