A Database for Arabic Handwritten Text Image Recognition and Writer Identification

Anis Mezghani; Slim Kanoun; Maher Khemakhem; Haikal El Abed; IEEE

doi:10.1109/ICFHR.2012.155

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A Database for Arabic Handwritten Text Image Recognition and Writer Identification

Anis Mezghani, Slim Kanoun, Maher Khemakhem, Haikal El Abed and IEEE

13TH INTERNATIONAL CONFERENCE ON FRONTIERS IN HANDWRITING RECOGNITION (ICFHR 2012), pp.399-402

International Conference on Handwriting Recognition

01/01/2012

DOI: https://doi.org/10.1109/ICFHR.2012.155

Abstract

Computer Science

Computer Science, Artificial Intelligence

Computer Science, Information Systems

Science & Technology

Technology

Standard databases play essential roles for evaluating and comparing results obtained by different groups of researchers. In this paper, an Arabic Handwritten Text Images Database written by Multiple Writers (AHTID/MW) is introduced. This database can be used for research in the recognition of Arabic handwritten text with open vocabulary, word segmentation and writer identification. The AHTID/MW contains 3710 text lines and 22896 words written by 53 native writers of Arabic. In addition, ground truth annotation is provided for each text image. The database is freely available for worldwide researchers.

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Details

Title: A Database for Arabic Handwritten Text Image Recognition and Writer Identification
Creators - without role: Anis Mezghani - University of Sfax
Slim Kanoun - University of Sfax
Maher Khemakhem - University of Sfax
Haikal El Abed - Technische Universität Braunschweig
IEEE
Publication Details: 13TH INTERNATIONAL CONFERENCE ON FRONTIERS IN HANDWRITING RECOGNITION (ICFHR 2012), pp.399-402
Series: International Conference on Handwriting Recognition
Publisher: IEEE
Number of pages: 4
Identifiers: 9934625208331
Academic Unit: King Abdulaziz University
Language: English
Resource Type: Conference proceeding