IEEE Transactions on Pattern Analysis and Machine Intelligence
A Note on Park and Chin's Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computers in Biology and Medicine
Order acceptance using genetic algorithms
Computers and Operations Research
Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network
Expert Systems with Applications: An International Journal
Note: Decomposition of binary morphological structuring elements based on genetic algorithms
Computer Vision and Image Understanding
Find multi-objective paths in stochastic networks via chaotic immune PSO
Expert Systems with Applications: An International Journal
Genetic algorithms for task scheduling problem
Journal of Parallel and Distributed Computing
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This paper proposed an improved decomposition approach for structuring elements of arbitrary shape. For the model of this method, we use the recursive model which decomposes a given structuring element into a variablesize matrix dilated by a fixed-size matrix and with union of a residue component, such procedures repeated until the variable-size matrix is smaller than a predefined threshold. For the algorithm of our method, we proposed an improved GA based on the ring topology of migration model and the power-rank fitness scaling strategy. The experiments demonstrate that our method is more robust than Park's method, Anelli's method, and Shih's method, and gave the final decomposition tree of different SE shapes such as the letter "V", heart, and umbrella.