Artières, T.

Dorissi, B.

Gallinari, P.

Marchand, J-M.

English

Hidden Markov Models (HMMs) have become within a few years the main technology for on line handwritten word recognition (HWR). We consider here segment models which generalize HMMs, these models aim at modeling the signal at a global level rather than at the frame level and have been shown to overcome standard HMMs in their modeling ability. We propose a new segment model which allows to automatically handle different writing styles. We compare our system on the isolated character set of the UNIPEN database to a reference system and a baseline segment model

ARTS repository - University of Groningen

STROKE LEVEL MODELING OF ON LINE HANDWRITING THROUGH MULTI­MODAL SEGMENTAL MODEL

https://pure.rug.nl/ws/files/2982489/paper-46-artieres.pdf

STROKE LEVEL MODELING OF ON LINE HANDWRITING THROUGH MULTIMODAL SEGMENTAL MODEL

Abstract

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ARTS repository - University of Groningen

STROKE LEVEL MODELING OF ON LINE HANDWRITING THROUGH MULTI­MODAL SEGMENTAL MODEL

Abstract

Similar works

Full text

Available Versions

ARTS repository - University of Groningen

STROKE LEVEL MODELING OF ON LINE HANDWRITING THROUGH MULTIMODAL SEGMENTAL MODEL