A list-processing approach to compute Voronoi diagrams and the Euclidean distance transform

被引:29
作者
Guan, WG [1 ]
Ma, SD
机构
[1] Victoria Univ Wellington, Dept Comp Sci, Wellington, New Zealand
[2] Chinese Acad Sci, Natl Lab Pattern Recognit, Beijing 100864, Peoples R China
基金
中国国家自然科学基金;
关键词
Voronoi transformation; Voronoi diagram; Euclidean distance; distance transformation; coherence;
D O I
10.1109/34.689306
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose an efficient Voronoi transform algorithm for constructing Voronoi diagrams using segment lists of rows. A significant feature of the algorithm is that it takes segments rather than pixels as the basic units to represent and propagate the nearest neighbor information. The segment lists are dynamically updated as they are scanned. A distance map can then be easily computed from the segment list representation of the Voronoi diagram. Experimental results have demonstrated its high efficiency. Extension of the algorithm to higher dimensions is also discussed.
引用
收藏
页码:757 / 761
页数:5
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