Poster Papers

Advances in Pattern Recognition

Volume 1451 of the series Lecture Notes in Computer Science pp 937-943

Date:

A hierarchical classifier for multifont digits

  • C. RodriguezAffiliated withComputer Architecture and Technology Department, The Basque Country University (UPV/EHU)
  • , J. MuguerzaAffiliated withComputer Architecture and Technology Department, The Basque Country University (UPV/EHU)
  • , M. NavarroAffiliated withComputer Architecture and Technology Department, The Basque Country University (UPV/EHU)
  • , A. ZárateAffiliated withComputer Architecture and Technology Department, The Basque Country University (UPV/EHU)
  • , J. I. Mar'inAffiliated withComputer Architecture and Technology Department, The Basque Country University (UPV/EHU)
  • , J. M. PérezAffiliated withComputer Architecture and Technology Department, The Basque Country University (UPV/EHU)

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Abstract

In this paper, the automatic recognition of broken and blurred, multifont typewritten digits in forms will be addressed. The classification, which is based on the utilization of a global feature, is divided in two phases: first, a minimum distance method (1-NN) is applied to provide a global classification of the patterns in a form; second, the patterns in the form previously classified are used to validate, or reject and reclassify them, on the basis of the mean distance to the predefined classes. In this way, a classification accuracy rate of 99.42% has been achieved.