DocumentCode :
1492877
Title :
Shape representation using a generalized potential field model
Author :
Ahuja, Narendra ; Chuang, Jen-Hui
Author_Institution :
Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA
Volume :
19
Issue :
2
fYear :
1997
fDate :
2/1/1997 12:00:00 AM
Firstpage :
169
Lastpage :
176
Abstract :
This paper is concerned with efficient derivation of the medial axis transform of a 2D polygonal region. Instead of using the shortest distance to the region border, a potential field model is used for computational efficiency. The region border is assumed to be charged and the valleys of the resulting potential field are used to estimate the axes for the medial axis transform. The potential valleys are found by following the force field, thus, avoiding 2D search. The potential field is computed in closed form using equations of the border segments. The simple Newtonian potential is shown to be inadequate for this purpose. A higher order potential is defined which decays faster with distance than the inverse of distance. It is shown that as the potential order becomes arbitrarily large, the axes approach those computed using the shortest distance to the border. Algorithms are given for the computation of axes, which can run in linear parallel time for part of the axes having initial guesses. Experimental results are presented for a number of examples
Keywords :
computer vision; image representation; optimisation; topology; transforms; 2D polygonal region; Newtonian potential; distance transform; generalized potential; medial axis transform; potential field model; potential valleys; shape representation; shortest distance; skeletonization; symmetric axis; topology; Computational efficiency; Concurrent computing; Equations; Shape; Topology; Transforms;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.574801
Filename :
574801
Link To Document :
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