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Computer vision, graphics, and image processing, v.34 no.3, 1986년, pp.344 - 371
Borgefors, Gunilla
In the first part of this paper optimal distance transformations are developed. Local neighborhoods of sizes up to 7 multiplied by 7 pixels are used. First real-valued distance transformations are considered, and then the best integer approximations of them are computed. A new distance transformation is presented, that is easily computed and has a maximal error of about 2%. In the second part of the paper six different distance transformations, both old and new, are used for a few different applications. These applications show both that the choice of distance transformation is important, and that any of the six transformations may be the right choice.(Edited author abstract)
Comput. Vision, Graphics Image Process. Borgefors 27 321 1984 10.1016/0734-189X(84)90035-5 Distance transformations in arbitrary dimensions
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Pattern Recognit. Rosenfeld 1 No. 1 33 1968 10.1016/0031-3203(68)90013-7 Distance functions on digital pictures
Borgefors 250 1983 3rd Scand. Conf. on Image Analysis Chamfering: A fast method for obtaining approximations of the Euclidean distance in N dimensions
J. Assoc. Comput. Mach. Montanari 15 600 1968 10.1145/321479.321486 A method for obtaining skeletons using a quasi-Euclidean distance
Rosenfeld Vol. 2 1982
Barrow 659 1977 Proc. 5th Int. Joint Conf. on Artif. Intell. Parametric correspondence and chamfer matching: Two new techniques for image matching
Comput. Graphics Image Process. Danielsson 14 227 1980 10.1016/0146-664X(80)90054-4 Euclidean distance mapping
Yamada 69 1984 Proc. 7th Int. Conf. on Pattern Recognit Complete Euclidean distance transformation by parallel operation
Borgefors 1175 1984 Proc. 7th Int. Conf. on Pattern Recognit. An improved version of the chamfer matching algorithm
Ahuja 1983
Organizing Geographical Objects Derived from a Digitized Map Jungert 1985
Computer J. Green 21 No. 2 168 1978 10.1093/comjnl/21.2.168 Computing Dirichlet tessellations in the plane
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