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This Guide to OCR for Arabic Scripts is the first book of its kind, specifically devoted to this emerging field. Topics and features: contains contributions from the leading researchers in the field; with a Foreword by Professor Bente Maegaard of the University of Copenhagen; presents a detailed overview of Arabic character recognition technology, covering a range of different aspects of pre-processing and feature extraction; reviews a broad selection of varying approaches, including HMM-based methods and a recognition system based on multidimensional recurrent neural networks; examines the…mehr

Produktbeschreibung
This Guide to OCR for Arabic Scripts is the first book of its kind, specifically devoted to this emerging field. Topics and features: contains contributions from the leading researchers in the field; with a Foreword by Professor Bente Maegaard of the University of Copenhagen; presents a detailed overview of Arabic character recognition technology, covering a range of different aspects of pre-processing and feature extraction; reviews a broad selection of varying approaches, including HMM-based methods and a recognition system based on multidimensional recurrent neural networks; examines the evaluation of Arabic script recognition systems, discussing data collection and annotation, benchmarking strategies, and handwriting recognition competitions; describes numerous applications of Arabic script recognition technology, from historical Arabic manuscripts to online Arabic recognition.
  • Produktdetails
  • Verlag: Springer, Berlin / Springer, London
  • Artikelnr. des Verlages: 80022015
  • Erscheinungstermin: August 2012
  • Englisch
  • Abmessung: 241mm x 160mm x 37mm
  • Gewicht: 1113g
  • ISBN-13: 9781447140719
  • ISBN-10: 1447140710
  • Artikelnr.: 35221042
Autorenporträt
Volker Märgner is Academic Director of the Institute for Communications Technology (IfN) at Technische Universität Braunschweig, Germany. He has over 30 years research experience in image processing, pattern recognition, and handwriting recognition. He developed the IfN/ENIT-database of Arabic handwritten names which is the reference for Arabic handwritten word recognition systems and organized competitions both together with Haikal El Abed.

Haikal El Abed is a Senior Research Engineer at the Institute for Communications Technology (IfN) at Technische Universität Braunschweig, Germany. He has more than 10 years research experience in pattern recognition and Arabic text recognition, on-line and off-line. He organizes competitions and works on the collection of databases.
Inhaltsangabe
Part I: Pre-Processing An Assessment of Arabic Handwriting Recognition Technology Sargur N. Srihari and Gregory Ball Layout Analysis of Arabic Script Documents Syed Saqib Bukhari
Faisal Shafait and Thomas M. Breuel A Multi-Stage Approach to Arabic Document Analysis Eugene Borovikov and Ilya Zavorin Pre-Processing Issues in Arabic OCR Zhixin Shi
Srirangaraj Setlur and Venu Govindaraju Segmentation of Ancient Arabic Documents Abdel Belaïd and Nazih Ouwayed Features for HMM-Based Arabic Handwritten Word Recognition Systems Laurence Likforman-Sulem
Ramy Al Hajj Mohammad
Chafic Mokbel
Fares Menasri
Anne-Laure Bianne-Bernard and Christopher Kermorvant Part II: Recognition Printed Arabic Text Recognition Irfan Ahmed
Sabri A. Mahmoud and Mohammed Tanvir Parvez Handwritten Arabic Word Recognition Using the IFN/ENIT-Database Mario Pechwitz
Haikal El Abed and Volker Märgner RWTH OCR: A Large Vocabulary Optical Character Recognition System for Arabic Scripts Philippe Dreuw
David Rybach
Georg Heigold and Hermann Ney Arabic Handwriting Recognition using Bernoulli HMMs Ihab Alkhoury
Adrià Giménez and Alfons Juan Handwritten Farsi Words Recognition Using Hidden Markov Models Puntis Jifroodian and Ching Y. Suen Offline Arabic Handwriting Recognition with Multidimensional Recurrent Neural Networks Alex Graves Application of Fractal Theory in Farsi/Arabic Document Analysis Saeed Mozaffari Multi-Stream Markov Models for Arabic Handwriting Recognition Yousri Kessentini
Thierry Paquet and AbdelMajid Ben Hamadou Towards Distributed Cursive Writing OCR Systems based on the Combination of Complementary Approaches Maher Khemakhem and Abdelfettah Belghith Part III: Evaluation Data Collection and Annotation for Arabic Document Analysis Ilya Zavorin and Eugene Borovikov Arabic Handwriting Recognition Competitions Volker Märgner and Haikal El Abed Benchmarking Strategy for Arabic Screen Rendered Word Recognition Fouad Slimane
Slim Kanoun
Jean Hennebert
Rolf Ingold
Adel M. Alimi and Jean Hennebert Part IV: Applications A Robust Word Spotting System for Historical Arabic Manuscripts Mohamed Cheriet and Reza Farrahi Moghaddam Arabic Text recognition using a Script-Independent Methodology: A Unified HMM-based Approach for Machine-print and Handwritten Text Premkumar Natarajan
Rohit Prasad
Huaigu Cao
Krishna Subramanian
Shirin Saleem
David Belanger
Shiv Vitaladevuni
Matin Kamali and Ehry MacRostie Arabic Handwriting Recognition Using VDHMM and Over-Segmentation Amlan Kundu and Tom Hines Online Arabic Databases and Applications Houcine Boubaker
Abdelkarim Elbaati
Najiba Tagougui
Haikal El Abed
Monji Kherallah and Adel M. Alimi Online Arabic Handwritten Words Recognition Based on HMM and Combination of Online and Offline Features Sherif Abdelazeem
Hesham M. Eraqi and Hany Ahmed