A new radical-based approach to online handwritten Chinese character recognition

Author

Ma, Long-Long ; Liu, Cheng-Lin

Author_Institution

Nat. Lab. of Pattern Recognition, Chinese Acad. of Sci., Beijing, China

fYear

2008

fDate

8-11 Dec. 2008

Firstpage

1

Lastpage

4

Abstract

This paper proposes a new radical-based approach for online handwritten chinese character recognition. The approach is novel in three respects: statistical classification of radicals, over-segmentation of characters into candidate radicals, and lexicon-driven recognition of characters. Currently, we have applied the approach to Chinese characters of left-right structure and are extending to other structures. Preliminary results on a sample set of 4,284 characters consisting of 1,118 radicals demonstrate the superiority of the proposed approach.

Keywords

handwritten character recognition; image classification; image segmentation; statistical analysis; candidate radical; character over-segmentation; lexicon-driven character recognition; online handwritten Chinese character recognition; radical-based approach; statistical radical classification; Automation; Character recognition; Hidden Markov models; Humans; Image segmentation; Laboratories; Neural networks; Pattern recognition; Shape; Statistical analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2008. ICPR 2008. 19th International Conference on

Conference_Location

Tampa, FL

ISSN

1051-4651

Print_ISBN

978-1-4244-2174-9

Electronic_ISBN

1051-4651

Type

conf

DOI

10.1109/ICPR.2008.4761207

Filename

4761207