Synthetic On-line Handwriting Generation by Distortions and Analogy - Archive ouverte HAL Access content directly
Conference Papers Year : 2007

Synthetic On-line Handwriting Generation by Distortions and Analogy


One of the difficulties to improve on the fly writer-dependent handwriting recognition systems is the lack of data available at the beginning of the adapting phase. In this paper we explore three possible strategies to generate synthetic handwriting characters from few samples of a writer. We explore in this paper both classical image distortions and two original ways to generate on-line handwritten characters: distortions based on specificities of the on-line handwriting and a generation based on analogical proportion. The experimentations show that these three approaches generate different distortions which are complementary. Indeed the combination of them allows to achieve using only 4 original characters for the learning phase a mean of 91.3% of recognition rate for 12 writers.
Fichier principal
Vignette du fichier
IGS07_final_version.pdf (166.64 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

inria-00300700 , version 1 (18-07-2008)
inria-00300700 , version 2 (16-01-2019)


  • HAL Id : inria-00300700 , version 2


Harold Mouchère, Sabri Bayoudh, Eric Anquetil, Laurent Miclet. Synthetic On-line Handwriting Generation by Distortions and Analogy. in 13th Conference of the International Graphonomics Society (IGS2007), Nov 2007, Melbourne, Australia. pp.10-13. ⟨inria-00300700v2⟩
420 View
126 Download


Gmail Facebook X LinkedIn More