Khoury, Ihab; Giménez, Adrià; Juan, Alfons; Andrés-Ferrer, Jesús Window Repositioning for Printed Arabic Recognition Journal Article Pattern Recognition Letters, 51 , pp. 86–93, 2015, ISSN: 0167-8655. Abstract | Links | BibTeX | Tags: Bernoulli HMMs, Printed Arabic Recognition, Repositioning, Sliding window @article{Kho14,
title = {Window Repositioning for Printed Arabic Recognition},
author = {Ihab Khoury and Adrià Giménez and Alfons Juan and Jesús Andrés-Ferrer},
url = {http://dx.doi.org/10.1016/j.patrec.2014.08.009},
issn = {0167-8655},
year = {2015},
date = {2015-01-01},
journal = {Pattern Recognition Letters},
volume = {51},
pages = {86--93},
abstract = {Bernoulli HMMs are conventional HMMs in which the emission probabilities are modeled with Bernoulli mixtures. They have recently been applied, with good results, in off-line text recognition in many languages, in particular, Arabic. A key idea that has proven to be very effective in this application of Bernoulli HMMs is the use of a sliding window of adequate width for feature extraction. This idea has allowed us to obtain very competitive results in the recognition of both Arabic handwriting and printed text. Indeed, a system based on it ranked first at the ICDAR 2011 Arabic recognition competition on the Arabic Printed Text Image (APTI) database. More recently, this idea has been refined by using repositioning techniques for extracted windows, leading to further improvements in Arabic handwriting recognition. In the case of printed text, this refinement led to an improved system which ranked second at the ICDAR 2013 second competition on APTI, only at a marginal distance from the best system. In this work, we describe the development of this improved system. Following evaluation protocols similar to those of the competitions on APTI, exhaustive experiments are detailed from which state-of-the-art results are obtained.},
keywords = {Bernoulli HMMs, Printed Arabic Recognition, Repositioning, Sliding window},
pubstate = {published},
tppubtype = {article}
}
Bernoulli HMMs are conventional HMMs in which the emission probabilities are modeled with Bernoulli mixtures. They have recently been applied, with good results, in off-line text recognition in many languages, in particular, Arabic. A key idea that has proven to be very effective in this application of Bernoulli HMMs is the use of a sliding window of adequate width for feature extraction. This idea has allowed us to obtain very competitive results in the recognition of both Arabic handwriting and printed text. Indeed, a system based on it ranked first at the ICDAR 2011 Arabic recognition competition on the Arabic Printed Text Image (APTI) database. More recently, this idea has been refined by using repositioning techniques for extracted windows, leading to further improvements in Arabic handwriting recognition. In the case of printed text, this refinement led to an improved system which ranked second at the ICDAR 2013 second competition on APTI, only at a marginal distance from the best system. In this work, we describe the development of this improved system. Following evaluation protocols similar to those of the competitions on APTI, exhaustive experiments are detailed from which state-of-the-art results are obtained. |
