TY  - CONF
ID  - slim08:cimca
T1  - Duration Models for Arabic Text Recognition using Hidden Markov Models
A1  - Slimane, Fouad
A1  - Ingold, Rolf
A1  - Alimi, Adel Mohamed
A1  - Hennebert, Jean
TI  - International Conference on Computational Intelligence for Modelling, Control and Automation (CIMCA 08), Vienna, Austria
Y1  - 2008
SP  - 838
EP  - 843
UR  - http://www.hennebert.org/download/publications/cimca-2008-Duration_Models_for_Arabic_Text_Recognition_using_Hidden_Markov_Models.pdf
M2  - doi: 10.1109/CIMCA.2008.229
KW  - HMM
KW  - image analysis
KW  - OCR
N2  - We present in this paper a system for recognition of printed Arabic text based on Hidden Markov Models (HMM). While HMMs have been successfully used in the past for such a task, we report here on significant improvements of the recognition performance with the introduction of minimum and maximum duration models. The improvements allow us to build a system working in open vocabulary mode, i.e., without any limitations on the size of the vocabulary. The evaluation of our system is performed using HTK (Hidden Markov Model Toolkit) on a database of word images that are synthetically generated
ER  -