The efficient algorithms for achieving Euclidean distance transformation

被引:27
作者
Shih, FY [1 ]
Wu, YT [1 ]
机构
[1] New Jersey Inst Technol, Comp Vis Lab, Coll Comp Sci, Newark, NJ 07102 USA
关键词
distance transformation (DT); Euclidean distance; image processing; mathematical morphology;
D O I
10.1109/TIP.2004.826098
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Euclidean distance transformation (EDT) is used to convert a digital binary image consisting of object (foreground) and nonobject (background) pixels into another image where each pixel has a value of the minimum Euclidean distance from nonobject pixels. In this paper, the improved iterative erosion algorithm is proposed to avoid the redundant calculations in the iterative erosion algorithm. Furthermore, to avoid the iterative operations, the two-scan-based algorithm by a deriving approach is developed for achieving EDT correctly and efficiently in a constant time. Besides, we discover when obstacles appear in the image, many algorithms cannot achieve the correct EDT except our two-scan-based algorithm. Moreover, the two-scan-based algorithm does not require the additional cost of preprocessing or relative-coordinates recording.
引用
收藏
页码:1078 / 1091
页数:14
相关论文
共 24 条
[1]   DISTANCE TRANSFORMATIONS IN DIGITAL IMAGES [J].
BORGEFORS, G .
COMPUTER VISION GRAPHICS AND IMAGE PROCESSING, 1986, 34 (03) :344-371
[2]   DISTANCE TRANSFORMATIONS IN ARBITRARY DIMENSIONS [J].
BORGEFORS, G .
COMPUTER VISION GRAPHICS AND IMAGE PROCESSING, 1984, 27 (03) :321-345
[3]   Fast Euclidean distance transformation by propagation using multiple neighborhoods [J].
Cuisenaire, O ;
Macq, B .
COMPUTER VISION AND IMAGE UNDERSTANDING, 1999, 76 (02) :163-172
[4]   EUCLIDEAN DISTANCE MAPPING [J].
DANIELSSON, PE .
COMPUTER GRAPHICS AND IMAGE PROCESSING, 1980, 14 (03) :227-248
[5]   Constant-time algorithm for the Euclidean distance transform on reconfigurable meshes [J].
Datta, A ;
Soundaralakshmi, S .
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2001, 61 (10) :1439-1455
[6]   Two fast euclidean distance transformations in Z2 based on sufficient propagation [J].
Eggers, H .
COMPUTER VISION AND IMAGE UNDERSTANDING, 1998, 69 (01) :106-116
[7]  
GIARDINA C, 1988, MORPHOLOGICAL METHOD
[8]   IMAGE-ANALYSIS USING MATHEMATICAL MORPHOLOGY [J].
HARALICK, RM ;
STERNBERG, SR ;
ZHUANG, XH .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1987, 9 (04) :532-550
[9]   A EUCLIDEAN DISTANCE TRANSFORM USING GRAYSCALE MORPHOLOGY DECOMPOSITION [J].
HUANG, CT ;
MITCHELL, OR .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1994, 16 (04) :443-448
[10]   A morphological approach to shortest path planning for rotating objects [J].
Pei, SC ;
Lai, CL ;
Shih, FY .
PATTERN RECOGNITION, 1998, 31 (08) :1127-1138