Discrimination of similar characters with Quadratic Compound Mahalanobis Function

Masato Suzuki, Nei Kato, Yoshiaki Nemoto, Hiroshi Ichimura

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

CMF is an efficient function in distinguishing a character from similar ones. This distinction is performed by correcting the Mahalanobis distance using feature vectors projected onto a certain subspace. However, this approach may have some limitations for the projective space, because the decision boundary surface of two similar characters is generally very complicated, There is also a method to estimate the decision boundary surface of two similar characters using nonlinear conversion, but the degree of variance-covariance matrix used in this estimation is very large. In this paper, we propose a CMF applied quadratic nonlinear conversion. We refer to our proposed method as the Quadratic Compound Mahalanobis Function (QCMF). It is shown that the QCMF can discriminate similar characters with a smaller amount of computation than discrimination with quadratic nonlinear conversion, and that in recognition experiments with similar characters, the accuracy of a recognition system with QCMF is better than that with CMF.

Original languageEnglish
Pages (from-to)11-20
Number of pages10
JournalSystems and Computers in Japan
Volume33
Issue number5
DOIs
Publication statusPublished - 2002 May 1
Externally publishedYes

Keywords

  • ETL9B
  • Handprinted kanji character recognition
  • Nonlinear conversion
  • Quadratic compound Mahalanobis function
  • Similar characters

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture
  • Computational Theory and Mathematics

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