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

Calatroni, Luca and van Gennip, Yves and Schönlieb, Carola-Bibiane and Rowland, Hannah M. and Flenner, Arjuna (2016) Graph clustering, variational image segmentation methods and Hough transform scale detection for object measurement in images. Journal of Mathematical Imaging and Vision . ISSN 1573-7683

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Abstract

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 presented in 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.

Item Type: Article
Additional Information: The final publication is available at link.springer.com via http://dx.doi.org/10.1007/s10851-016-0678-0
Keywords: Graph clustering, Discrete Ginzburg–Landau functional, Image segmentation, Scale detection, Hough transform
Schools/Departments: University of Nottingham UK Campus > Faculty of Science > School of Mathematical Sciences
Identification Number: https://doi.org/10.1007/s10851-016-0678-0
Depositing User: Van Gennip, Yves
Date Deposited: 23 Sep 2016 13:29
Last Modified: 25 Sep 2016 04:16
URI: http://eprints.nottingham.ac.uk/id/eprint/37060

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