A handwritten character recognition system using directional element feature and asymmetric Mahalanobis distance

Author

Kato, Nei ; Suzuki, Masato ; Omachi, Shin Ichiro ; Aso, Hirotomo ; Nemoto, Yoshiaki

Author_Institution

Graduate Sch. of Inf. Sci., Tohoku Univ., Sendai, Japan

Volume

21

Issue

3

fYear

1999

fDate

3/1/1999 12:00:00 AM

Firstpage

258

Lastpage

262

Abstract

This paper presents a precise system for handwritten Chinese and Japanese character recognition. Before extracting directional element feature (DEF) from each character image, transformation based on partial inclination detection (TPID) is used to reduce undesired effects of degraded images. In the recognition process, city block distance with deviation (CBDD) and asymmetric Mahalanobis distance (AMD) are proposed for rough classification and fine classification. With this recognition system, the experimental result of the database ETL9B reaches to 99.42%

Keywords

handwritten character recognition; image classification; AMD; CBDD; DEF; ETL9B database; TPID; asymmetric Mahalanobis distance; city block distance; degraded images; deviation; directional element feature; directional element feature extraction; fine classification; handwritten Chinese character recognition; handwritten Japanese character recognition; image transformation; partial inclination detection; rough classification; Character recognition; Cities and towns; Degradation; Feature extraction; Handwriting recognition; Image converters; Image recognition; Nonlinear distortion; Pattern matching; Pattern recognition;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.754617

Filename

754617