Online Japanese Character Recognition Using Trajectory-Based Normalization and Direction Feature Extraction

Cheng-Lin Liu 1, 2 Xiang-Dong Zhou 1, 2
1 NLPR - National Laboratory of Pattern Recognition [Beijing]
2 LIAMA - Pattern
Abstract : This paper describes an online Japanese character recognition system using advanced techniques of pattern normalization and direction feature extraction. The normalization of point coordinates and the decomposition of direction elements are directly performed on online trajectory, and therefore, are computationally efficient. We compare one-dimensional and pseudo two-dimensional (pseudo 2D) normalization methods, as well as direction features from original pattern and from normalized pattern. In experiments on the TUAT HANDS databases, the pseudo 2D normalization methods yielded superior performance, while direction features from original pattern and from normalized pattern made little difference.
Keywords : Direction feature extraction Online character recognition Trajectorybased normalization Pseudo 2D normalization Direction feature extraction.
Type de document :
Communication dans un congrès
Guy Lorette. Tenth International Workshop on Frontiers in Handwriting Recognition, Oct 2006, La Baule (France), Suvisoft, 2006
Liste complète des métadonnées
https://hal.inria.fr/inria-00108303
Contributeur : Ist Rennes <>
Soumis le : vendredi 20 octobre 2006 - 13:03:23
Dernière modification le : mardi 24 avril 2018 - 13:36:32
Document(s) archivé(s) le : mardi 6 avril 2010 - 20:16:40

Fichier

cr100374111345.pdf

Identifiants

  • HAL Id : inria-00108303, version 1

Collections

IWFHR10 | INRIA | CIRAD | INRA | LIAMA

Citation

Cheng-Lin Liu, Xiang-Dong Zhou. Online Japanese Character Recognition Using Trajectory-Based Normalization and Direction Feature Extraction. Guy Lorette. Tenth International Workshop on Frontiers in Handwriting Recognition, Oct 2006, La Baule (France), Suvisoft, 2006. 〈inria-00108303〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

950

Téléchargements de fichiers

1117

Contact


archive-ouverte@inria.fr