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Automatic extraction of human-recognizable shape and execution prototypes of handwritten characters

Authors
Journal
Pattern Recognition
0031-3203
Publisher
Elsevier
Publication Date
Volume
36
Issue
7
Identifiers
DOI: 10.1016/s0031-3203(02)00259-5
Keywords
  • Prototype Extraction
  • Allograph
  • Execution Plan
  • Handwriting Recognition
  • Fuzzy Artmap
  • Lvq
Disciplines
  • Computer Science

Abstract

Abstract The novel prototype extraction method presented in this paper aims to advancing in the comprehension of handwriting generation and improving on-line recognition systems. The extraction process is performed in two stages. First, using Fuzzy ARTMAP we group character instances according to classification criteria. Then, an algorithm refines these groups and computes the prototypes. Experimental results on the UNIPEN international database show that the proposed system is able to extract a low number of prototypes that are easily recognizable. In addition, the extraction method is able to condense knowledge that can be successfully used to initialize an LVQ-based recognizer, achieving an average recognition rate of 90.15%, comparable to that reached by human readers.

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