Matching structural shape descriptions using genetic algorithms

被引：0
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作者：
Indian Inst of Technology, New Delhi, India [1 ]
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来源：
Pattern Recognit | / 9卷 / 1451-1462期
关键词：
Computational complexity - Genetic algorithms - Graph theory - Mathematical operators - Optimization - Problem solving;
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摘要：
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.
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