# Graph clustering, variational image segmentation methods and Hough transform scale detection for object measurement in images

arXiv: https://arxiv.org/abs/1602.08574 · HTML: https://mlsanity.com/paper/1602.08574/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Feb 2016.

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

- [An Empirical Study of Graph-Based Approaches for Semi-Supervised Time Series Classification](https://mlsanity.com/paper/2104.08153/) (2021)
- [Joint reconstruction-segmentation on graphs](https://mlsanity.com/paper/2208.05834/) (2022)

## Abstract (arXiv)

We consider the problem of scale detection in images where a region of interest is present together with a measurement tool (e.g. a ruler). For the segmentation part, we focus on the graph based method by Flenner and Bertozzi which reinterprets classical continuous Ginzburg-Landau minimisation models in a totally discrete framework. To overcome the numerical difficulties due to the large size of the images considered we use matrix completion and splitting techniques. The scale on the measurement tool is detected via a Hough transform based algorithm. The method is then applied to some measurement tasks arising in real-world applications such as zoology, medicine and archaeology.