Gap-Sensitive Segmentation and Restoration of Digital Images

dc.contributor.authorSobiecki, Andreen_US
dc.contributor.authorJalba, Andreien_US
dc.contributor.authorBoda, Danielen_US
dc.contributor.authorDiaconeasa, Adrianaen_US
dc.contributor.authorTelea, Alexandruen_US
dc.contributor.editorRita Borgo and Wen Tangen_US
dc.date.accessioned2014-12-15T15:53:06Z
dc.date.available2014-12-15T15:53:06Z
dc.date.issued2014en_US
dc.description.abstractMany methods exist for removing defects such as gaps, cracks, and disconnections from digital shapes. However, most such methods have several limitations, such as removing both erroneous and important shape details, or requiring non-trivial effort from the end user in the form of manual delineation or parameter setting. In this paper, we propose a technique for removing defects such as internal gaps and cracks from 2D and 3D digital shapes. For this, we first classify gaps as boundary detail (to be preserved) and interior errors (to be removed), based on a heuristic that uses the gap position with respect the medial axis of the simplified shape. Next, we remove error gaps using an efficient distance-based filling. We illustrate our method on robust segmentation and hair removal tasks for skin imaging, and compare our results with a number of relevant techniques in this area.en_US
dc.description.seriesinformationComputer Graphics and Visual Computing (CGVC)en_US
dc.identifier.isbn978-3-905674-70-5en_US
dc.identifier.urihttps://doi.org/10.2312/cgvc.20141200en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.3 [Computer Graphics]en_US
dc.subjectPicture/Image Generationâ ''Line and curve generationen_US
dc.titleGap-Sensitive Segmentation and Restoration of Digital Imagesen_US
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