Direkoglu, Cem and Dahyot, Rozenn and Manzke, Michael (2012) On Using Anisotropic Diffusion for Skeleton Extraction. International Journal of Computer Vision, 100. pp. 170-189. ISSN 0920-5691

Preview

Download (3MB) | Preview

Abstract

We present a novel and effective skeletonization algorithm for binary and gray-scale images, based on the anisotropic heat diffusion analogy. We diffuse the image in the direction normal to the feature boundaries and also allow tangential diffusion (curvature decreasing diffusion) to contribute slightly. The proposed anisotropic diffusion provides a high quality medial function in the image: it removes noise and preserves prominent curvatures of the shape along the level-sets (skeleton features). The skeleton strength map, which provides the likelihood of a point to be part of the skeleton, is defined by the mean curvature measure. Finally, thin and binary skeleton is obtained by non-maxima suppression and hysteresis thresholding of the skeleton strength map. Our method outperforms the most related and the popular methods in skeleton extraction especially in noisy conditions. Results show that the proposed approach is better at handling noise in images and preserving the skeleton features at the centerline of the shape.

Item Type:	Article
Keywords:	Skeletonization; Feature extraction; Heat flow; Computer vision;
Academic Unit:	Faculty of Science and Engineering > Computer Science
Item ID:	15120
Identification Number:	https://doi.org/10.1007/s11263-012-0540-9
Depositing User:	Rozenn Dahyot
Date Deposited:	14 Dec 2021 15:30
Journal or Publication Title:	International Journal of Computer Vision
Publisher:	Springer
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

Repository Staff Only(login required)

Item control page

Downloads

Origin of downloads