Skip to Main content Skip to Navigation
Conference papers

Towards Arabic Handwritten Word Recognition via Probabilistic Graphical Models

Akram Khémiri 1 Afef Kacem 1 Abdel Belaïd 2 
2 READ - Recognition of writing and analysis of documents
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : —In this work, we propose a novel system for the recognition of handwritten Arabic words. It is evolved based on horizontal-vertical Hidden Markov Model and Dynamic Bayesian Network Model. Our strategy consists of looking for various HMM architectures and selecting those which provide the best recognition performance. Experiments on handwritten Arabic words from IFN/ENIT strongly support the feasibility of the proposed approach. The recognition rates achieve 92.19% with horizontal-vertical Hidden Markov Model and 88.82% with a Dynamic Bayesian Network.
Document type :
Conference papers
Complete list of metadata

Cited literature [16 references]  Display  Hide  Download

https://hal.inria.fr/hal-01111751
Contributor : Abdel Belaid Connect in order to contact the contributor
Submitted on : Tuesday, February 3, 2015 - 3:39:50 PM
Last modification on : Saturday, October 16, 2021 - 11:26:09 AM
Long-term archiving on: : Saturday, April 15, 2017 - 11:42:18 PM

File

ICFHR-Khémiri-Kacem-Belaid-Ca...
Files produced by the author(s)

Identifiers

Collections

Citation

Akram Khémiri, Afef Kacem, Abdel Belaïd. Towards Arabic Handwritten Word Recognition via Probabilistic Graphical Models. International Conference on Frontiers in Handwriting Recognition, Sep 2014, Crete, Greece. ⟨10.1109/ICFHR.2014.119⟩. ⟨hal-01111751⟩

Share

Metrics

Record views

4420

Files downloads

195