Article ID Journal Published Year Pages File Type
525850 Computer Vision and Image Understanding 2013 15 Pages PDF
Abstract

Skeletons are notoriously sensitive to contour noise, and an effective filtering scheme is needed in any practical situation, where skeletons are involved. In this article, we introduce a new discrete framework that allows us to define and compute families of filtered Euclidean skeletons, in 2D as well as in 3D or higher dimensions. We prove several properties of our skeletonization scheme, in particular the preservation of topological characteristics and the stability with respect to parameter changes.

► New approach for computing hierarchies of Euclidean skeletons. ► Guarantees on stability and topology preservation. ► Purely discrete approach, well suited to the processing of digital 2D and 3D images. ► Flexible scheme, allowing for many variants.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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