DocumentCode :
1304088
Title :
Angular bisector network, a simplified generalized Voronoi diagram: application to processing complex intersections in biomedical images
Author :
Cloppet, Florence ; Oliva, Jean-Michel ; Stamon, George
Author_Institution :
Lab. SIP-CRIPS, Univ. Rene Descartes, Paris, France
Volume :
22
Issue :
1
fYear :
2000
fDate :
1/1/2000 12:00:00 AM
Firstpage :
120
Lastpage :
128
Abstract :
One of the major goals of computer vision is the research and the development of flexible methods for shape description. A large group of shape description techniques is given by heuristic approaches, which yield acceptable results in the description of simple shapes and regions. In this case, objects are represented by a planar graph with nodes symbolizing subregions from region decomposition, and region shape is then described by the graph properties. In the paper, the angular bisector network (ABN), a descriptor of polygonal shape, is used to automatically detect intersections between neurites of cell structures. Some properties of the ABN, such as linear algebraic complexity, easy extraction of characteristic points, etc., are very useful and experimental results are promising
Keywords :
computational complexity; computational geometry; computer vision; graph theory; medical image processing; angular bisector network; biomedical images; complex intersections; flexible methods; graph properties; heuristic approaches; linear algebraic complexity; polygonal shape; shape description; simplified generalized Voronoi diagram; Application software; Atherosclerosis; Biomedical computing; Biomedical imaging; Costs; Graph theory; Robots; Senior members; Shape; Skeleton;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.824824
Filename :
824824
Link To Document :
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