Variational Pruning of Medial Axes of Planar Shapes

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dc.contributor.authorRong, Peteren_US
dc.contributor.authorJu, Taoen_US
dc.contributor.editorMemari, Pooranen_US
dc.contributor.editorSolomon, Justinen_US
dc.date.accessioned2023-06-30T06:18:41Z
dc.date.available2023-06-30T06:18:41Z
dc.date.issued2023
dc.description.abstractMedial axis (MA) is a classical shape descriptor in graphics and vision. The practical utility of MA, however, is hampered by its sensitivity to boundary noise. To prune unwanted branches from MA, many definitions of significance measures over MA have been proposed. However, pruning MA using these measures often comes at the cost of shrinking desirable MA branches and losing shape features at fine scales. We propose a novel significance measure that addresses these shortcomings. Our measure is derived from a variational pruning process, where the goal is to find a connected subset of MA that includes as many points that are as parallel to the shape boundary as possible. We formulate our measure both in the continuous and discrete settings, and present an efficient algorithm on a discrete MA. We demonstrate on many examples that our measure is not only resistant to boundary noise but also excels over existing measures in preventing MA shrinking and recovering features across scales.en_US
dc.description.number5
dc.description.sectionheaders2D Geometry
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14902
dc.identifier.issn1467-8659
dc.identifier.pages11 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14902
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14902
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Computing methodologies -> Shape analysis
dc.subjectComputing methodologies
dc.subjectShape analysis
dc.titleVariational Pruning of Medial Axes of Planar Shapesen_US
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