Skip to Main content Skip to Navigation
Conference papers

Online Character Segmentation Method for Unconstrained Handwriting Strings Using Off-stroke Features

Abstract : In this paper, an online character segmentation method for unconstrained strings is proposed. To recognize unconstrained-expression strings such as those in phrases and informal notations, we designed physical features of segmented patterns, in particular, off-stroke features. Segmented-pattern likelihood was also defined from these features using a probabilistic model. Evaluations using a digital pen system showed that the character segmentation rates were 97.8%, 91.7%, and 75.6% of numerals, Japanese characters, and all characters (numerals, alphabets, symbols, and Japanese characters), respectively.
Complete list of metadata

Cited literature [8 references]  Display  Hide  Download

https://hal.inria.fr/inria-00104383
Contributor : Anne Jaigu <>
Submitted on : Friday, October 6, 2006 - 2:07:18 PM
Last modification on : Friday, October 6, 2006 - 2:16:45 PM
Long-term archiving on: : Tuesday, April 6, 2010 - 6:50:20 PM

Identifiers

  • HAL Id : inria-00104383, version 1

Collections

Citation

Naohiro Furukawa, Junko Tokuno, Hisashi Ikeda. Online Character Segmentation Method for Unconstrained Handwriting Strings Using Off-stroke Features. Tenth International Workshop on Frontiers in Handwriting Recognition, Université de Rennes 1, Oct 2006, La Baule (France). ⟨inria-00104383⟩

Share

Metrics

Record views

184

Files downloads

412