Representative Graph Generation for Graph-Based Character Recognition

Research output: Contribution to journalArticlepeer-review

Abstract

In graph-based pattern recognition, representative graph influences the performances of recognition and clustering. In this paper, we propose a learning method for generating a representative graph of a set of graphs by constructing graph unions with merging corresponding vertices and edges. Those corresponding vertices and edges are obtained using common vertices of a set. The proposed method includes extracting common vertices and correspondences of vertices. To show the validly of the proposed method, we applied the proposed method to pattern recognition problems with character graph database and graphs obtained from decorative character images.

Original languageEnglish
Pages (from-to)439-447
Number of pages9
JournalJournal of the Institute of Image Electronics Engineers of Japan
Volume40
Issue number3
DOIs
Publication statusPublished - 2011 Jan

Keywords

  • character recognition
  • graph clustering
  • graph-based pattern recognition
  • representative graph

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Electrical and Electronic Engineering

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