A genetic algorithm based region sampling for selection of local features in handwritten digit recognition application

@article{Das2012AGA,
  title={A genetic algorithm based region sampling for selection of local features in handwritten digit recognition application},
  author={Nibaran Das and Ram Sarkar and Subhadip Basu and Mahantapas Kundu and Mita Nasipuri and Dipak Kumar Basu},
  journal={Appl. Soft Comput.},
  year={2012},
  volume={12},
  pages={1592-1606}
}
Identification of local regions from where optimal discriminating features can be extracted is one of the major tasks in the area of pattern recognition. To locate such regions different kind of region sampling techniques are used in the literature. There is no standard methodology to identify exactly such regions. Here we have proposed a methodology where local regions of varying heights and widths are created dynamically. Genetic algorithm (GA) is then applied on these local regions to sample… CONTINUE READING

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  • Other popular optimization techniques like simulated annealing (SA) and hill climbing (HC) have also been evaluated with the same data set and maximum recognition accuracies were found to be 97%, 96.7% and 96.7% for GA, SA and HC, respectively.

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