Showing papers by "Haikal El Abed published in 2013"
25 Aug 2013
TL;DR: This paper describes the Arabic Recognition Competition: Multi-font Multi-size Digitally Represented Text held in the context of the 12th International Conference on Document Analysis and Recognition (ICDAR'2013), during August 25-28, 2013, Washington DC, United States of America.
Abstract: This paper describes the Arabic Recognition Competition: Multi-font Multi-size Digitally Represented Text held in the context of the 12th International Conference on Document Analysis and Recognition (ICDAR'2013), during August 25-28, 2013, Washington DC, United States of America. This competition has used the freely available Arabic Printed Text Image (APTI) database. A first edition took place in ICDAR'2011. In this edition, four groups with six systems are participating in the competition. The systems are compared using the recognition rates at character and word levels. The systems were tested in a blind manner using set 6 of APTI database. A short description of the participating groups, their systems, the experimental setup, and the observed results are presented.
25 citations
09 Sep 2013
TL;DR: This database can be used to evaluate the system that recognizes Arabic printed texts with an open vocabulary and may be also used for research in word segmentation and font identification.
Abstract: This paper presents a real database for the Arabic printed text recognition, APTID / MF (Arabic Printed Text Image Database / Multi-Font).This database can be used to evaluate the system that recognizes Arabic printed texts with an open vocabulary. APTID / MF may be also used for research in word segmentation and font identification. APTID / MF is obtained from 387 pages of Arabic printed documents scanned with grayscale format and 300 dpi resolutions. From this documents, 1,845 text-blocks have been extracted. In addition ground truth file is provided for each texts-block. APTID / MF also includes an Arabic printed character image dataset made up of 27,402 samples. The database is freely available to interested researchers.
22 citations
15 Feb 2013
TL;DR: A method which combines some baseline extraction techniques used in literature was presented to provide a fine estimation of baseline in Arabic handwritten text-lines and the AHTID/MW database was extended by a baseline ground truth annotation.
Abstract: Baseline extraction is one of the most important phases for handwriting recognition. Due to the complexity of the Arabic scripts, baseline detection of Arabic handwritten text-lines is a difficult task compared to other languages. In this work, a method which combines some baseline extraction techniques used in literature was presented to provide a fine estimation of baseline in Arabic handwritten text-lines. For evaluation purpose, the AHTID/MW database was extended by a baseline ground truth annotation. The database is freely available for researchers worldwide which enable other researchers to test their baseline detection systems.
2 citations