AQC0417

Nanopublication — Computational Image Analysis - AQC0417

Claim 1: Computational Image Analysis - AQC0417

Analysis record [3]: The [1] lady at the café, Paris (AQC0417) [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]: 1536x2048 pixels. Analysis date: 2026-02-04.

Color Analysis

Rank Color Hex % Family Name
1 211008 17.0 red-orange very dark gray
2 D77341 13.7 orange peru
3 D89150 12.7 orange sandybrown
4 CC652B 12.3 orange chocolate
5 25273B 11.3 violet very dark gray
6 A04423 9.0 orange burnt sienna
7 464C5B 7.0 blue-violet grayish purple
8 717950 6.6 yellow-green dimgray
9 71311A 6.4 orange russet
10 E1A774 4.0 orange darksalmon
11 957A85 0.3 red dusty mauve [Accent]
12 AC8E41 0.3 yellow-orange peru [Accent]
13 AEA162 0.3 yellow ochre [Accent]

Color Families:

Family %
orange 58.1
red-orange 17.0
violet 11.3
blue-violet 7.0
yellow-green 6.6
red 0.3
yellow-orange 0.3
yellow 0.3

Accent Colors:

Hex Family Name Chroma
957A85 red dusty mauve 12.2
AC8E41 yellow-orange peru 44.0
AEA162 yellow ochre 34.2

Texture Analysis

Metric Value
Global Roughness 0.202
Mean Local Roughness 0.006
Roughness Uniformity 0.012
Edge Density 0.013
Mean Gradient Magnitude 0.056
Gradient Variance 0.027
Gradient Smoothness 0.0
Directional Coherence 0.253
Pattern Complexity 0.095
Pattern Repetition 1.0
Detail Frequency Ratio 0.568
Spatial Variation 0.091
Texture Consistency 0.772

Brightness & Contrast Analysis

Metric Value
Mean Brightness 0.375
Brightness Variance 0.202
Brightness Uniformity 0.461
Brightness Skewness -0.155
Brightness Entropy 7.399
Rms Contrast 0.202
Michelson Contrast 1.0
Weber Contrast 0.869
Mean Local Contrast 0.007
Contrast Uniformity 0.0
Dynamic Range 0.863
Effective Dynamic Range 0.6
Shadow Percentage 41.55
Midtone Percentage 53.97
Highlight Percentage 4.48
Shadow Clipping 0.0
Highlight Clipping 0.0
Tonal Balance 0.17
Fine Contrast 0.003
Medium Contrast 0.009
Coarse Contrast None
Multiscale Contrast Ratio 1.0
Edge Contrast 0.056
Contrast Clustering 0.228

Spatial Distribution Analysis

Metric Value
Spatial Coherence 0.714
Color Clustering 0.59
Color Transition Smoothness 0.818
Transition Uniformity 0.788
Sharp Transition Ratio 0.1
Transition Directionality 0.233
Mean Saturation 0.634
Saturation Variance 0.039
Low Saturation Ratio 0.066
Medium Saturation Ratio 0.479
High Saturation Ratio 0.454
Saturation Clustering 0.999
Hue Concentration 0.683
Complementary Balance 0.092
Analogous Dominance 0.798
Temperature Bias 0.717

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 (2023). The lady at the café, Paris — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0417.html

[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2023/01/the-lady-at-the-cafe-paris_4qe.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)

385c60a4ff54b53ab009bcedcb9795976293f561b18b4afec3056877ec6ab705