Dear guest, welcome to this publication database. As an anonymous user, you will probably not have edit rights. Also, the collapse status of the topic tree will not be persistent. If you like to have these and other options enabled, you might ask Admin (Ivan Eggel) for a login account.
 [BibTeX] [RIS]
Duration Models for Arabic Text Recognition using Hidden Markov Models
Type of publication: Inproceedings
Citation: slim08:cimca
Booktitle: International Conference on Computational Intelligence for Modelling, Control and Automation (CIMCA 08), Vienna, Austria
Year: 2008
Pages: 838--843
URL: http://www.hennebert.org/downl...
DOI: 10.1109/CIMCA.2008.229
Abstract: 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
Keywords: HMM, image analysis, OCR
Authors Slimane, Fouad
Ingold, Rolf
Alimi, Adel Mohamed
Hennebert, Jean
Added by: []
Total mark: 0
Attachments
    Notes
      Topics