Distance Functions Based on Multiple Types of Weighted Steps Combined with Neighborhood Sequences-Reference-Cited by-同舟云学术

Distance Functions Based on Multiple Types of Weighted Steps Combined with Neighborhood Sequences

Published:2018-03-16 Issue:8 Volume:60 Page:1209-1219
ISSN:0924-9907
Container-title:Journal of Mathematical Imaging and Vision
language:en
Short-container-title:J Math Imaging Vis

Author:

Nagy Benedek^ORCID,Strand Robin,Normand Nicolas

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Geometry and Topology,Computer Vision and Pattern Recognition,Condensed Matter Physics,Modeling and Simulation,Statistics and Probability

Link

http://link.springer.com/article/10.1007/s10851-018-0805-1/fulltext.html

Reference22 articles.

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2. Breu, H., Kirkpatrick, D., Werman, M.: Linear time Euclidean distance transform algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 17(5), 529–533 (1995). https://doi.org/10.1109/34.391389

3. Celebi, M.E., Celiker, F., Kingravi, H.A.: On Euclidean norm approximations. Pattern Recognit. 44(2), 278–283 (2011). https://doi.org/10.1016/j.patcog.2010.08.028

4. Coeurjolly, D., Vacavant, A.: Separable distance transformation and its applications. In: Digital Geometry Algorithms. Theoretical Foundations and Applications to Computational Imaging, Lecture Notes in Computational Vision and Biomechanics, vol 2, pp. 189–214 (2012). https://doi.org/10.1007/978-94-007-4174-4_7

5. Danielsson, P.E.: Euclidean distance mapping. Comput. Graph. Image Process. 14(3), 227–248 (2008). https://doi.org/10.1016/0146-664X(80)90054-4

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