Generation of handwriting by active shape modeling and Global Local Approximation (GLA) adaptation

Ashirwad Chowriappa, Ricardo N. Rodrigues, Thenkurussi Kesavadas, Venu Govindaraju, Ann Bisantz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The generation of handwriting is a complex task. In order to accommodate for the large variations involved in handwritten words deformable templates need to be used. In this paper we propose a handwriting model, based on Active shape modeling (ASM). In a two-step generation process, a template-based ASM generates characters and a Gaussian mixture regression (GMR) model concatenates the generated characters. For real time generation of cursive handwriting an adaptation of Global local approximation (GLA) methodology is used to fit the generated models.

Original languageEnglish (US)
Title of host publicationProceedings - 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010
Pages206-211
Number of pages6
DOIs
StatePublished - 2010
Externally publishedYes
Event12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010 - Kolkata, India
Duration: Nov 16 2010Nov 18 2010

Publication series

NameProceedings - 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010

Other

Other12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010
Country/TerritoryIndia
CityKolkata
Period11/16/1011/18/10

Keywords

  • Active shape modeling
  • CAPTCHA generation
  • Global local approximation
  • Handwriting generation

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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