Nanopublication — Computational Image Analysis - AQC0390
Claim 1: Computational Image Analysis - AQC0390
K-means clustering analysis [3] (10 colors) performed on artwork The [1] driver of Tram 28, Lisbon (AQC0390) [2] by Arnaud Quercy [2] on 2025-11-04. Documentation includes: color families, texture roughness, brightness distribution, spatial coherence.
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: 2025-11-04.
## 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 (2022). The driver of Tram 28, Lisbon — Catalog raisonné. https://arnaudquercy.art/en/catalogue-raisonne/AQC0390.html
[2] Quercy, A. (2025). Untitled - Gallery. https://artquamanima.com/en/artworks/2022/01/the-driver-of-tram-28-lisbon_4fw.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
Where this work lives
Thematic Elements
Epistemic profile
| Claim type | computational analysis |
|---|---|
| Voice | third person |
| Epistemic status | empirical measurement |
| Methodology | computational analysis |
| Certainty | high |
Checksum (SHA-256)
a68effed0429856b7617d421138cb9a4833d846f61082bb2625c448edeb0d3b0