Generation of Handwriting by Active Shape Modeling and Global Local Approximation (GLA) Adaptation
- Resource Type
- Conference
- Authors
- Chowriappa, Ashirwad; Rodrigues, Ricardo N.; Kesavadas, Thenkurussi; Govindaraju, Venu; Bisantz, Ann
- Source
- 2010 12th International Conference on Frontiers in Handwriting Recognition Frontiers in Handwriting Recognition (ICFHR), 2010 International Conference on. :206-211 Nov, 2010
- Subject
- Computing and Processing
Communication, Networking and Broadcast Technologies
Shape
Approximation methods
Analytical models
Active shape model
Adaptation model
Deformable models
Active shape modeling
global local approximation
handwriting generation
CAPTCHA generation
- Language
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.