By Topic

Fast homotopy-preserving skeletons using mathematical morphology

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
L. Ji ; Western Gen. Hospital, Edinburgh, UK ; J. Piper

Two algorithms for skeletonization of 2-D binary images, each of which explicitly separates the two major aspects of skeletonization are described: the identification of points critical to shape representation, and the identification of further points necessary to preserve homotopy. Sets of points critical to shape representation are found by eroding the original image I with a nested sequence of structuring elements Ei. By choosing appropriate { Ei} and D, a structuring element, either algorithm is capable of producing a variety of skeletons corresponding to different distance functions. A sufficient condition is given for the original image to be reconstructed from the skeleton. In the case of the first algorithm, there are few restrictions on the set of structuring elements. It uses a simple search strategy to find points whose removal would alter homotopy. The second, faster, algorithm has a more constructional approach to finding points necessary for preserving homotopy, which limits it to a more restricted set of structuring elements than the first algorithm. However, it may still be used with a variety of distance functions

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:14 ,  Issue: 6 )