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

Research output: Contribution to journalArticle

175 Citations (Scopus)

Abstract

This paper presents a precise system for handwritten Chinese and Japanese character recognition. Before extracting directional element feature (DBF) 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%. Index Terms-Handwritten Chinese and Japanese character recognition directional element feature city block distance with deviation asymmetric Mahalanobis distance ETL9B.

Original languageEnglish
Pages (from-to)258-262
Number of pages5
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume21
Issue number3
DOIs
Publication statusPublished - 1999 Dec 1

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

Fingerprint Dive into the research topics of 'A handwritten character recognition system using directional element feature and asymmetric mahalanobis distance'. Together they form a unique fingerprint.

  • Cite this