BINARY AND GREY-VALUE SKELETONS: METRICS AND ALGORITHMS

Publisher Website
Google Scholar
Abstract
A metric defines the distance between any two points. The “natural” metrics of the digital world do not approximate the Euclidean metric of the continuous world well. Skeletonization (sometimes named topology preserving shrinking or homotopic thinning) is one example in which this leads to unacceptable results. In the present work we propose and demonstrate skeletonization using path-based metrics which are a better approximation of the Euclidean metric. Moreover, we achieve a good performance on sequential processors by processing each pixel only once in the calculations of binary (Hilditch) and grey-value (upper) skeletons.

This publication has 0 references indexed in Scilit: