A classifier of similar characters using compound Mahalanobis function based on difference subspace

Junichi Hirayama, Hidehisa Nakayama, Nei Kato

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

To distinguish similar characters, it is preferable to construct a classifier using a projective feature space which differentiates two similar categories. The classifier CMF has been proposed for a discriminant function, in similar characters recognition. In the CMF, a subspace is constructed by some eigenvectors, that corresponds to the smallest eigenvalues, is applied as projective feature space. A difference vector of two class-mean feature vectors are assumed as the difference between two similar categories, the CMF is constructed by projecting a feature vector onto this difference vector. In this paper, we propose new discriminant function expanding the CMF. In proposed method, we treat the Difference Subspace, which is difference between two subspaces as difference between two similar categories. The efficiency of the proposed new discriminant function has been demonstrated in similar characters recognition through extensive experiments on hand-written Japanese characters derived from the ETL9B database.

Original languageEnglish
Title of host publicationProceedings - 9th International Conference on Document Analysis and Recognition, ICDAR 2007
Pages432-436
Number of pages5
DOIs
Publication statusPublished - 2007 Dec 1
Event9th International Conference on Document Analysis and Recognition, ICDAR 2007 - Curitiba, Brazil
Duration: 2007 Sep 232007 Sep 26

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
Volume1
ISSN (Print)1520-5363

Other

Other9th International Conference on Document Analysis and Recognition, ICDAR 2007
CountryBrazil
CityCuritiba
Period07/9/2307/9/26

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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