Computer Vision, Graphics, and Image Processing
Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
Morphological methods in image and signal processing
Morphological methods in image and signal processing
Morphological Shape Decomposition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sequential Operations in Digital Picture Processing
Journal of the ACM (JACM)
Digital Picture Processing
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
On Computing the Exact Euclidean Distance Transform on Rectangular and Hexagonal Grids
Journal of Mathematical Imaging and Vision
Decomposition of Separable Concave Structuring Functions
Journal of Mathematical Imaging and Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Euclidean distance transformation in two scans using a 3 × 3 neighborhood
Computer Vision and Image Understanding
Jump flooding in GPU with applications to Voronoi diagram and distance transform
I3D '06 Proceedings of the 2006 symposium on Interactive 3D graphics and games
Skeletonization based on error reduction
Pattern Recognition
2D Euclidean distance transform algorithms: A comparative survey
ACM Computing Surveys (CSUR)
Binary-image comparison with local-dissimilarity quantification
Pattern Recognition
3-D chamfer distances and norms in anisotropic grids
Image and Vision Computing
Anti-aliased Euclidean distance transform
Pattern Recognition Letters
An efficient euclidean distance transform
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
Euclidean distance transform of digital images in arbitrary dimensions
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
FPGA-based architecture for real time segmentation and denoising of HD video
Journal of Real-Time Image Processing
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A fast and exact Euclidean distance transformation using decomposed grayscale morphological operators is presented. Applied on a binary image, a distance transformation assigns each object pixel a value that corresponds to the shortest distance between the object pixel and the background pixels. It is shown that the large structuring element required for the Euclidean distance transformation can be easily decomposed into 3/spl times/3 windows. This is possible because the square of the Euclidean distance matrix changes uniformly both in the vertical and horizontal directions. A simple extension for a 3D Euclidean distance transformation is discussed. A fast distance transform for serial computers is also presented. Acting like thinning algorithms, the version for serial computers focuses operations only on the potential changing pixels and propagates from the boundary of objects, significantly reducing execution time. Nonsquare pixels can also be used in this algorithm. An example application, shape filtering using arbitrary sized circular dilation and erosion, is discussed. Rotation-invariant basic morphological operations can be done using this example application.