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Matching structural shape descriptions using genetic algorithms
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DOI：10.1016/S0031-3203(96)00181-1.png)
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摘要
En 中文
This paper presents a genetic algorithm for solving the problem of structural shape matching. Both sequential and parallel versions of the algorithm have been presented. The genetic operators-reproduction, crossover and mutation-have been constructed for this specific problem. A new variation of the crossover operator, called the color crossover, is presented. This operator has resulted in significant improvement in runtime and algorithm efficiency. Parallelization has been achieved using an ''island'' model, with several subpopulations and occasional migration. A complete framework for an object recognition system using this genetic algorithm has been presented. Encouraging experimental results have been obtained. (C) 1997 Pattern Recognition Society. Published by Elsevier Science Ltd.
Keyword:
structural descriptions
graph isomorphism
genetic algorithms
parallelization
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期刊
IF:
7.6
论文数:
1.4W
被引数:
4.5W
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