Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
Computing Voronoi diagrams in digital pictures
Pattern Recognition Letters
Computing distance transformations in convex and non-convex domains
Pattern Recognition
An Efficient Uniform Cost Algorithm Applied to Distance Transforms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Partial Shape Classification Using Contour Matching in Distance Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Best simple octagonal distances in digital geometry
Journal of Approximation Theory
Generating skeletons and centerlines from the distance transform
CVGIP: Graphical Models and Image Processing
The Euclidean distance transform in arbitrary dimensions
Pattern Recognition Letters
A unified distance transform algorithm and architecture
Machine Vision and Applications
Digital Picture Processing
Intelligent Autonomous Systems, An International Conference
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Distance transformation (DT) has been widely used for image matching and shape analysis. In this paper, a parallel algorithm for computing distance transformation is presented. First, it is shown that the algorithm has an execution time of 6N - 4 cycles, for an N × N image using a parallel architecture that requires [N/2] parallel processors. By doing so, the real time requirement is fulfilled and its execution time is independent of the image contents. In addition, a partition method is developed to process an image when the parallel architecture has a fixed number of processing elements (PEs); say two or more. The total execution time for an N × N image by employing a fixed number of PEs is 2[N2/M + 2(M -1)], when M is the fixed number of PEs.