Connected component labeling of binary images on a mesh connected massively parallel processor
Computer Vision, Graphics, and Image Processing
Algorithms for Image Component Labeling on SIMD Mesh-Connected Computers
IEEE Transactions on Computers
Fast Image Labeling Using Local Operators on Mesh-Connected Computers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Introduction to parallel algorithms and architectures: array, trees, hypercubes
Introduction to parallel algorithms and architectures: array, trees, hypercubes
Parallel Architectures and Algorithms for Image Component Labeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
The SIMD model of parallel computation
The SIMD model of parallel computation
Parallel algorithms for regular architectures: meshes and pyramids
Parallel algorithms for regular architectures: meshes and pyramids
Connectivity in Digital Pictures
Journal of the ACM (JACM)
On shrinking binary picture patterns
Communications of the ACM
Handbook of Computer Vision Algorithms in Image Algebra
Handbook of Computer Vision Algorithms in Image Algebra
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We study two classical connectivity-preserving parallel shrinking algorithms proposed to recognize and label two-dimensional connected components of binary images. The algorithms we consider were developed by Beyer [Recognition of topological invariants by iterative arrays, Ph.D. Thesis, MIT, 1969, p. 144] and Levialdi [Commun. ACM 15 (1) (1972) 7] independently for the purpose of shrinking 4-connected and 8-connected components of binary images in linear time, respectively. It is shown that those two independently developed algorithms are closely related and in a sense they are in a dual relation such that, for any initially given binary image and its inverted one, one algorithm produces, simultaneously, an image which is dual of the one produced by the other, step-by-step.