Finite topology as applied to image analysis
Computer Vision, Graphics, and Image Processing
A topological approach to digital topology
American Mathematical Monthly
A unified linear-time algorithm for computing distance maps
Information Processing Letters
New Notions for Discrete Topology
DCGI '99 Proceedings of the 8th International Conference on Discrete Geometry for Computer Imagery
Discrete bisector function and Euclidean skeleton in 2D and 3D
Image and Vision Computing
Exact medial axis with euclidean distance
Image and Vision Computing
A new 3d parallel thinning scheme based on critical kernels
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
2D Euclidean distance transform algorithms: A comparative survey
ACM Computing Surveys (CSUR)
Discrete 2D and 3D euclidean medial axis in higher resolution
Image and Vision Computing
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The notion of skeleton plays a major role in shape analysis Some usually desirable characteristics of a skeleton are: sufficient for the reconstruction of the original object, centered, thin and homotopic The Euclidean Medial Axis presents all these characteristics in a continuous framework In the discrete case, the Exact Euclidean Medial Axis (MA) is also sufficient for reconstruction and centered It no longer preserves homotopy but it can be combined with a homotopic thinning to generate homotopic skeletons The thinness of the MA, however, may be discussed In this paper we present the definition of the Exact Euclidean Medial Axis on Higher Resolution which has the same properties as the MA but with a better thinness characteristic, against the price of rising resolution We provide an efficient algorithm to compute it.