[IPOL discuss] [IPOL announce] new article: Finding the Skeleton of 2D Shape and Contours: Implementation of Hamilton-Jacobi Skeleton

[announcements about the IPOL journal]

A new article is available in IPOL: http://www.ipol.im/pub/art/2021/296/


Yuchen He, Sung Ha Kang, and Luis Álvarez,
Finding the Skeleton of 2D Shape and Contours: Implementation of 
Hamilton-Jacobi Skeleton,
Image Processing On Line, 11 (2021), pp. 18–36.
https://doi.org/10.5201/ipol.2021.296

Abstract
This paper presents the details of the flux-ordered thinning algorithm, 
which we refer to as the Hamilton-Jacobi Skeleton (HJS). It computes the 
skeleton of any binary 2D shape. It is based on the observation that the 
skeleton points have low average outward flux of the gradient of the 
distance transform. The algorithm starts by computing the distance 
function and approximating the flux values for all pixels inside the 
shape. Then a procedure called homotopy preserving thinning iteratively 
removes points with high flux while preserving the homotopy of the 
shape. In this paper, we implement the distance transform using a fast 
sweeping algorithm. We present numerical experiments to show the 
performance of HJS applied to various shapes. We point out that HJS 
serves as a multi-scale shape representation, a homotopy classifier, and 
a deficiency detector for binary 2D shapes. We also quantitatively 
evaluate the shape reconstructed from the medial axis obtained by HJS.




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