Fast Euclidean distance transformation in two scans using a 3 x 3 neighborhood

被引：72

作者：

Shih, FY ^{[1
]}

Wu, YT ^{[1
]}

机构：

[1] New Jersey Inst Technol, Coll Comp Sci, Comp Vis Lab, Newark, NJ 07102 USA

来源：

COMPUTER VISION AND IMAGE UNDERSTANDING | 2004年 / 93卷 / 02期

关键词：

distance transformation; Euclidean distance; image processing; object representation;

D O I：

10.1016/j.cviu.2003.09.004

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Cuisenaire and Macq [Comp. Vis. Image Understand., 76(2) (1999) 163] proposed a fast Euclidean distance transformation (EDT) by propagation using multiple neighborhoods and bucket sorting. To save the time for bucket sorting and to reduce the complexity of multiple neighborhoods, we propose a new, simple and fast EDT in two scans using a 3 x 3 neighborhood. By recording the relative x- and y-coordinates, an optimal two-scan algorithm can be developed to achieve the EDT correctly and efficiently in a constant time without iterations. (C) 2003 Elsevier Inc. All rights reserved.

引用

页码：195 / 205

页数：11