Online arabic handwriting recognition using hidden markov models

Fadi Biadsy; Jihad El-Sana; Nizar Y Habash

doi:10.7916/D8NZ8H35

Online arabic handwriting recognition using hidden markov models

Fadi Biadsy
, Jihad El-Sana
, Nizar Y Habash

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Online handwriting recognition of Arabic script is a difficult problem since it is naturally both cursive and unconstrained. The analysis of Arabic script is further complicated in comparison to Latin script due to obligatory dots/stokes that are placed above or below most letters. This paper introduces a Hidden Markov Model (HMM) based system to provide solutions for most of the difficulties inherent in recognizing Arabic script including: letter connectivity, position-dependent letter shaping, and delayed strokes. This is the first HMM-based solution to online Arabic handwriting recognition. We report successful results for writer-dependent and writer-independent word recognition.

Original language	English
Title of host publication	Proceedings of the 10th International Workshop on Frontiers of Handwriting and Recognition
DOIs	https://doi.org/10.7916/D8NZ8H35
State	Published - 2006

Access to Document

10.7916/D8NZ8H35

Cite this

@inproceedings{b0d35558c8cd492dbbc285adc5307b33,

title = "Online arabic handwriting recognition using hidden markov models",

abstract = "Online handwriting recognition of Arabic script is a difficult problem since it is naturally both cursive and unconstrained. The analysis of Arabic script is further complicated in comparison to Latin script due to obligatory dots/stokes that are placed above or below most letters. This paper introduces a Hidden Markov Model (HMM) based system to provide solutions for most of the difficulties inherent in recognizing Arabic script including: letter connectivity, position-dependent letter shaping, and delayed strokes. This is the first HMM-based solution to online Arabic handwriting recognition. We report successful results for writer-dependent and writer-independent word recognition.",

author = "Fadi Biadsy and Jihad El-Sana and Habash, \{Nizar Y\}",

year = "2006",

doi = "10.7916/D8NZ8H35",

language = "English",

booktitle = "Proceedings of the 10th International Workshop on Frontiers of Handwriting and Recognition",

}

TY - GEN

T1 - Online arabic handwriting recognition using hidden markov models

AU - Biadsy, Fadi

AU - El-Sana, Jihad

AU - Habash, Nizar Y

PY - 2006

Y1 - 2006

N2 - Online handwriting recognition of Arabic script is a difficult problem since it is naturally both cursive and unconstrained. The analysis of Arabic script is further complicated in comparison to Latin script due to obligatory dots/stokes that are placed above or below most letters. This paper introduces a Hidden Markov Model (HMM) based system to provide solutions for most of the difficulties inherent in recognizing Arabic script including: letter connectivity, position-dependent letter shaping, and delayed strokes. This is the first HMM-based solution to online Arabic handwriting recognition. We report successful results for writer-dependent and writer-independent word recognition.

AB - Online handwriting recognition of Arabic script is a difficult problem since it is naturally both cursive and unconstrained. The analysis of Arabic script is further complicated in comparison to Latin script due to obligatory dots/stokes that are placed above or below most letters. This paper introduces a Hidden Markov Model (HMM) based system to provide solutions for most of the difficulties inherent in recognizing Arabic script including: letter connectivity, position-dependent letter shaping, and delayed strokes. This is the first HMM-based solution to online Arabic handwriting recognition. We report successful results for writer-dependent and writer-independent word recognition.

U2 - 10.7916/D8NZ8H35

DO - 10.7916/D8NZ8H35

M3 - Conference contribution

BT - Proceedings of the 10th International Workshop on Frontiers of Handwriting and Recognition

ER -

Online arabic handwriting recognition using hidden markov models

Abstract

Access to Document

Fingerprint

Cite this