AQC1058 | NAN-COL000621

Nanopublication — Computational Image Analysis - AQC1058

Watercolor Study in D5 (power chord) No. 1

Claim 1: Computational Image Analysis - AQC1058

Analysis record: Watercolor Study in D5 (power chord) No. 1 (AQC1058) [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: 1665x2220 pixels. Analysis date: 2026-07-13.

A) Color Analysis

Rank Color Hex % Family Name
1 B0682F 18.4 orange burnt sienna
2 AB6022 17.2 orange burnt sienna
3 983E02 15.3 orange russet
4 A65914 12.8 orange burnt sienna
5 B6713B 12.5 orange peru
6 A04C04 11.2 orange russet
7 8E3101 7.3 orange russet
8 050000 3.2 black black
9 6F380A 1.2 orange russet
10 3E1A04 1.0 orange very dark orange
11 7E0501 0.3 red-orange maroon [Accent]

Color Families:

Family %
orange 96.8
black 3.2
red-orange 0.3

Accent Colors:

Hex Family Name Chroma
7E0501 red-orange maroon 59.0

B) Texture Analysis

Metric Value
Global Roughness 0.103
Mean Local Roughness 0.015
Roughness Uniformity 0.01
Edge Density 0.007
Mean Gradient Magnitude 0.109
Gradient Variance 0.017
Gradient Smoothness 0.0
Directional Coherence 0.015
Pattern Complexity 0.131
Pattern Repetition 1.0
Detail Frequency Ratio 0.624
Spatial Variation 0.056
Texture Consistency 0.353

C) Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.393
Brightness Variance 0.103
Brightness Uniformity 0.739
Brightness Skewness -1.774
Brightness Entropy 6.234
Rms Contrast 0.103
Michelson Contrast 1.0
Weber Contrast 0.405
Mean Local Contrast 0.015
Contrast Uniformity 0.262
Dynamic Range 0.655
Effective Dynamic Range 0.263
Shadow Percentage 22.815
Midtone Percentage 77.185
Highlight Percentage 0.0
Shadow Clipping 1.46
Highlight Clipping 0.0
Tonal Balance 0.0
Fine Contrast 0.01
Medium Contrast 0.018
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.109
Contrast Clustering 0.647

D) Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.737
Color Clustering 0.293
Color Transition Smoothness 0.711
Transition Uniformity 0.854
Sharp Transition Ratio 0.1
Transition Directionality 0.014
Mean Saturation 0.836
Saturation Variance 0.025
Low Saturation Ratio 0.015
Medium Saturation Ratio 0.129
High Saturation Ratio 0.856
Saturation Clustering 0.998
Hue Concentration 0.992
Complementary Balance 0.001
Analogous Dominance 0.996
Temperature Bias 0.996

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 D5 (power chord) No. 1 - Catalogue Raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC1058.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)

26b94059c3484aa02279ecbdb142df0ea03a3e550821a013044ad1ab649d9292

This page in other formats

PDF · Markdown · Français