IEEE Transactions on Pattern Analysis and Machine Intelligence
Decomposition of Arbitrarily Shaped Morphological Structuring Elements
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Combinatorial Optimization Technique for the Sequential Decomposition of Erosions and Dilations
Journal of Mathematical Imaging and Vision
A Note on Park and Chin's Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Decomposition of binary morphological structuring elements based on genetic algorithms
Computer Vision and Image Understanding
An Embedded Real-Time Surveillance System: Implementation and Evaluation
Journal of Signal Processing Systems
Note: Decomposition of binary morphological structuring elements based on genetic algorithms
Computer Vision and Image Understanding
Decomposition of arbitrary gray-scale morphological structuring elements
Pattern Recognition
Computationally efficient, one-pass algorithm for morphological filters
Journal of Visual Communication and Image Representation
Recursive structure element decomposition using migration fitness scaling genetic algorithm
ICSI'11 Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I
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A number of different algorithms have been described in the literature for the decomposition of both convex binary morphological structuring elements and a specific subset of nonconvex ones. Nevertheless, up to now no deterministic solutions have been found to the problem of decomposing arbitrarily shaped structuring elements. This work presents a new stochastic approach based on Genetic Algorithms in which no constraints are imposed on the shape of the initial structuring element, nor assumptions are made on the elementary factors, which are selected within a given set.