AQC1054 | NAN-COL000617

Nanopublication — Computational Image Analysis - AQC1054

Watercolor Study in C5 (power chord) No. 2

Claim 1: Computational Image Analysis - AQC1054

Analysis record: Watercolor Study in C5 (power chord) No. 2 (AQC1054) [1] by Arnaud Quercy [2], per IDS-CMP-2025 [3]. Method: k-means. Parameters: 10 colors. Metrics: color distribution, texture, brightness, spatial patterns. Completed: 2026-07-13.

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: 1664x2219 pixels. Analysis date: 2026-07-13.

A) Color Analysis

Rank Color Hex % Family Name
1 7A2F0D 15.2 orange russet
2 AD6838 13.6 orange burnt sienna
3 6E2607 12.5 orange maroon
4 943804 10.9 orange russet
5 1A0B09 10.5 red-orange black
6 B37143 10.3 orange peru
7 A75F2D 9.1 orange burnt sienna
8 823B19 7.5 orange russet
9 2E1412 5.7 red-orange very dark gray
10 8E4E2C 4.8 orange burnt sienna

Color Families:

Family %
orange 83.8
red-orange 16.2

B) Texture Analysis

Metric Value
Global Roughness 0.139
Mean Local Roughness 0.013
Roughness Uniformity 0.007
Edge Density 0.007
Mean Gradient Magnitude 0.098
Gradient Variance 0.01
Gradient Smoothness 0.0
Directional Coherence 0.01
Pattern Complexity 0.129
Pattern Repetition 1.0
Detail Frequency Ratio 0.619
Spatial Variation 0.091
Texture Consistency 0.5

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.309
Brightness Variance 0.139
Brightness Uniformity 0.55
Brightness Skewness -0.226
Brightness Entropy 6.672
Rms Contrast 0.139
Michelson Contrast 0.987
Weber Contrast 0.831
Mean Local Contrast 0.013
Contrast Uniformity 0.38
Dynamic Range 0.612
Effective Dynamic Range 0.439
Shadow Percentage 60.392
Midtone Percentage 39.608
Highlight Percentage 0.0
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.008
Medium Contrast 0.016
Coarse Contrast 0.023
Multiscale Contrast Ratio 0.362
Edge Contrast 0.098
Contrast Clustering 0.5

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.759
Color Clustering 0.414
Color Transition Smoothness 0.737
Transition Uniformity 0.913
Sharp Transition Ratio 0.1
Transition Directionality 0.01
Mean Saturation 0.771
Saturation Variance 0.022
Low Saturation Ratio 0.0
Medium Saturation Ratio 0.387
High Saturation Ratio 0.613
Saturation Clustering 0.999
Hue Concentration 0.993
Complementary Balance 0.0
Analogous Dominance 1.0
Temperature Bias 1.0

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). Watercolor Study in C5 (power chord) No. 2 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC1054.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

Checksum (SHA-256)

60009cd43ab3616a8496a7e9698cb1e36ac871a717de36c25dbb4d30b36608c6

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