Qualitative adaptation of subspace method for character recognition

Shinichiro Omachi; Hirotomo Aso

doi:10.1002/1520-684X(20001115)31:12<1::AID-SCJ1>3.0.CO;2-U

Qualitative adaptation of subspace method for character recognition

Shinichiro Omachi, Hirotomo Aso

ENG - Communications Engineering

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

A new algorithm based on the subspace method for recognizing poor-quality character images is proposed. In many cases, damage caused by photocopying or facsimile occurs accidentally. It is difficult to solve this kind of damage by statistical methods. We investigate how distribution of data changes because of blurring. Then the eigenvectors and eigenvalues that are used in the subspace method and multiple similarity method are modified according to the change. The effectiveness of the proposed algorithm is shown by the experimental results.

Original language	English
Pages (from-to)	1-10
Number of pages	10
Journal	Systems and Computers in Japan
Volume	31
Issue number	12
DOIs	https://doi.org/10.1002/1520-684X(20001115)31:12<1::AID-SCJ1>3.0.CO;2-U
Publication status	Published - 2000 Nov 15

ASJC Scopus subject areas

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

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10.1002/1520-684X(20001115)31:12<1::AID-SCJ1>3.0.CO;2-U

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AB - A new algorithm based on the subspace method for recognizing poor-quality character images is proposed. In many cases, damage caused by photocopying or facsimile occurs accidentally. It is difficult to solve this kind of damage by statistical methods. We investigate how distribution of data changes because of blurring. Then the eigenvectors and eigenvalues that are used in the subspace method and multiple similarity method are modified according to the change. The effectiveness of the proposed algorithm is shown by the experimental results.

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Qualitative adaptation of subspace method for character recognition

Abstract

ASJC Scopus subject areas

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