Comparative performance analysis of stroke correspondence search methods for stroke-order free online multi-stroke character recognition

Wenjie Cai, Seiichi Uchida, Hiroaki Sakoe

Research output: Contribution to journalArticle

Abstract

For stroke-order free online multi-stroke character recognition, stroke-to-stroke correspondence search between an input pattern and a reference pattern plays an important role to deal with the stroke-order variation. Although various methods of stroke correspondence have been proposed, no comparative study for clarifying the relative superiority of those methods has been done before. In this paper, we firstly review the approaches for solving the stroke-order variation problem. Then, five representative methods of stroke correspondence proposed by different groups, including cube search (CS), bipartite weighted matching (BWM), individual correspondence decision (ICD), stable marriage (SM), and deviation-expansion model (DE), are experimentally compared, mainly in regard of recognition accuracy and efficiency. The experimental results on an online Kanji character dataset, showed that 99.17%, 99.17%, 96.37%, 98.54%, and 96.59% were attained by CS, BWM, ICD, SM, and DE, respectively as their recognition rates. Extensive discussions are made on their relative superiorities and practicalities.

Original languageEnglish
Pages (from-to)773-784
Number of pages12
JournalFrontiers of Computer Science
Volume8
Issue number5
DOIs
Publication statusPublished - Oct 31 2014

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Character recognition
Character Recognition
Stroke
Comparative Analysis
Search Methods
Performance Analysis
Correspondence
Stable Marriage
Regular hexahedron
Deviation
Comparative Study
Experimental Results

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Comparative performance analysis of stroke correspondence search methods for stroke-order free online multi-stroke character recognition. / Cai, Wenjie; Uchida, Seiichi; Sakoe, Hiroaki.

In: Frontiers of Computer Science, Vol. 8, No. 5, 31.10.2014, p. 773-784.

Research output: Contribution to journalArticle

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