Database for Arabic Printed Text Recognition Research

Faten Kallel Jaiem; Slim Kanoun; Maher Khemakhem; Haikal El Abed; Jihain Kardoun

doi:10.1007/978-3-642-41181-6_26

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Database for Arabic Printed Text Recognition Research

Conference proceeding

Open access

Peer reviewed

Database for Arabic Printed Text Recognition Research

Faten Kallel Jaiem, Slim Kanoun, Maher Khemakhem, Haikal El Abed and Jihain Kardoun

IMAGE ANALYSIS AND PROCESSING (ICIAP 2013), PT 1, Vol.8156(1), pp.251-259

Lecture Notes in Computer Science

01/01/2013

DOI: https://doi.org/10.1007/978-3-642-41181-6_26

Abstract

Computer Science

Computer Science, Artificial Intelligence

Computer Science, Theory & Methods

Imaging Science & Photographic Technology

Science & Technology

Technology

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.

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Title: Database for Arabic Printed Text Recognition Research
Creators - without role: Faten Kallel Jaiem - University of Sfax
Slim Kanoun - University of Sfax
Maher Khemakhem - University of Sfax
Haikal El Abed - Technische Universität Braunschweig
Jihain Kardoun - University of Sfax
Contributors - without role: A Petrosino
Publication Details: IMAGE ANALYSIS AND PROCESSING (ICIAP 2013), PT 1, Vol.8156(1), pp.251-259
Series: Lecture Notes in Computer Science
Publisher: Springer Nature
Number of pages: 9
Identifiers: 9934260808331
Academic Unit: King Abdulaziz University
Language: English
Resource Type: Conference proceeding