Journal
JOURNAL OF MATHEMATICAL IMAGING AND VISION
Volume 57, Issue 2, Pages 269-291Publisher
SPRINGER
DOI: 10.1007/s10851-016-0678-0
Keywords
Graph clustering; Discrete Ginzburg-Landau functional; Image segmentation; Scale detection; Hough transform
Categories
Funding
- UK Engineering and Physical Sciences Research Council (EPSRC) [EP/H023348/1]
- EPSRC [EP/J009539/1, EP/M00483X/1]
- ONR grant [N0001415WX01350]
- Royal Society [RG64240]
- British Ecology Society [BES2322]
- Junior Research Fellowship from Churchill college
- Institute Research Fellowship at the Institute of Zoology
- Department of Zoology at the University of Cambridge
- Churchill College, Cambridge
- EPSRC [EP/J009539/1, EP/M00483X/1, EP/N014588/1] Funding Source: UKRI
- Alan Turing Institute [TU/B/000071] Funding Source: researchfish
- Engineering and Physical Sciences Research Council [EP/N014588/1, EP/M00483X/1, EP/J009539/1] Funding Source: researchfish
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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 Bertozzi and Flenner (Multiscale Model Simul 10(3):1090-1118, 2012) 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.
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