@inproceedings{457026111e044dbabfca7e09f68df0d3,
title = "Feature-preserving medial axis noise removal",
abstract = "This paper presents a novel technique for medial axis noise removal. The method introduced removes the branches generated by noise on an object{\textquoteright}s boundary without losing the fine features that are often altered or destroyed by current pruning methods. The algorithm consists of an intuitive threshold-based pruning process, followed by an automatic feature reconstruction phase that effectively recovers lost details without reintroducing noise. The result is a technique that is robust and easy to use. Tests show that the method works well on a variety of objects with significant differences in shape complexity, topology and noise characteristics.",
author = "Roger Tam and Wolfgang Heidrich",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2002.; 7th European Conference on Computer Vision, ECCV 2002 ; Conference date: 28-05-2002 Through 31-05-2002",
year = "2003",
doi = "10.1007/3-540-47967-8_45",
language = "English (US)",
isbn = "9783540437444",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "672--686",
editor = "Anders Heyden and Gunnar Sparr and Mads Nielsen and Peter Johansen",
booktitle = "Computer Vision - 7th European Conference on Computer Vision, ECCV 2002, Proceedings",
address = "Germany",
}