Guide to OCR for Arabic Scripts
(Sprache: Englisch)
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...
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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 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.
Klappentext zu „Guide to OCR for Arabic Scripts “
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.
Inhaltsverzeichnis zu „Guide to OCR for Arabic Scripts “
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
... mehr
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
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
... weniger
Autoren-Porträt von Volker Märgner, Haikal El Abed
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.
Bibliographische Angaben
- Autoren: Volker Märgner , Haikal El Abed
- 2012, XX, 592 Seiten, Masse: 16 x 24,1 cm, Gebunden, Englisch
- Herausgegeben: Volker Märgner, Haikal El Abed
- Verlag: Springer, Berlin
- ISBN-10: 1447140710
- ISBN-13: 9781447140719
Sprache:
Englisch
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