# Stochastic Geometry Models for Texture Synthesis of Machined Metallic Surfaces: Sandblasting and Milling

arXiv: https://arxiv.org/abs/2403.13439 · HTML: https://mlsanity.com/paper/2403.13439/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 40 references that are in the map.
- First posted on arXiv 20 Mar 2024.

## Builds on (most cited first, 6 of 6)

- [Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis](https://mlsanity.com/paper/1701.02096/) (2017)
- [A Theory of Generative ConvNet](https://mlsanity.com/paper/1602.03264/) (2016)
- [Cooperative Training of Descriptor and Generator Networks](https://mlsanity.com/paper/1609.09408/) (2016)
- [A survey of exemplar-based texture synthesis](https://mlsanity.com/paper/1707.07184/) (2017)
- [Crack Modeling via Minimum-Weight Surfaces in 3d Voronoi Diagrams](https://mlsanity.com/paper/2210.05093/) (2022)
- [Conditional Generative ConvNets for Exemplar-based Texture Synthesis](https://mlsanity.com/paper/1912.07971/) (2019)

## Built on by (most cited first, 2 of 2)

- [SYNOSIS: Image synthesis pipeline for machine vision in metal surface inspection](https://mlsanity.com/paper/2410.14844/) (2024)
- [Generative adversarial framework to calibrate excursion set models for the 3D morphology of all-solid-state battery cathodes](https://mlsanity.com/paper/2503.17171/) (2025)

## Abstract (arXiv)

Training defect detection algorithms for visual surface inspection systems requires a large and representative set of training data. Often there is not enough real data available which additionally cannot cover the variety of possible defects. Synthetic data generated by a synthetic visual surface inspection environment can overcome this problem. Therefore, a digital twin of the object is needed, whose micro-scale surface topography is modeled by texture synthesis models. We develop stochastic texture models for sandblasted and milled surfaces based on topography measurements of such surfaces. As the surface patterns differ significantly, we use separate modeling approaches for the two cases. Sandblasted surfaces are modeled by a combination of data-based texture synthesis methods that rely entirely on the measurements. In contrast, the model for milled surfaces is procedural and includes all process-related parameters known from the machine settings.