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Guide to OCR for Arabic Scripts

By Volker Märgner , Haikal El Abed

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This detailed overview of Arabic character recognition technology covers pre-processing and feature extraction; HMM-based methods; evaluation of OCR systems; and applications of recognition technology, from historical manuscripts to online Arabic recognition.

Full Description

  • ISBN13: 978-1-4471-4071-9
  • 610 Pages
  • User Level: Science
  • Publication Date: July 3, 2012
  • Available eBook Formats: PDF
  • eBook Price: $149.00
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Full Description
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.
Table of Contents

Table of Contents

  1. Part I: Pre
  2. Processing.
  3. An Assessment of Arabic Handwriting Recognition Technology.
  4. Layout Analysis of Arabic Script Documents.
  5. A Multi
  6. Stage Approach to Arabic Document Analysis.
  7. Pre
  8. Processing Issues in Arabic OCR.
  9. Segmentation of Ancient Arabic Documents.
  10. Features for HMM
  11. Based Arabic Handwritten Word Recognition Systems.
  12. Part II: Recognition.
  13. Printed Arabic Text Recognition.
  14. Handwritten Arabic Word Recognition Using the IFN/ENIT
  15. Database.
  16. RWTH OCR: A Large Vocabulary Optical Character Recognition System for Arabic Scripts.
  17. Arabic Handwriting Recognition using Bernoulli HMMs.
  18. Handwritten Farsi Words Recognition Using Hidden Markov Models.
  19. Offline Arabic Handwriting Recognition with Multidimensional Recurrent Neural Networks.
  20. Application of Fractal Theory in Farsi/Arabic Document Analysis.
  21. Multi
  22. Stream Markov Models for Arabic Handwriting Recognition.
  23. Towards Distributed Cursive Writing OCR Systems based on the Combination of Complementary Approaches.
  24. Part III: Evaluation.
  25. Data Collection and Annotation for Arabic Document Analysis.
  26. Arabic Handwriting Recognition Competitions.
  27. Benchmarking Strategy for Arabic Screen Rendered Word Recognition.
  28. Part IV: Applications.
  29. A Robust Word Spotting System for Historical Arabic Manuscripts.
  30. Arabic Text recognition using a Script
  31. Independent Methodology: A Unified HMM
  32. based Approach for Machine
  33. print and Handwritten Text.
  34. Arabic Handwriting Recognition Using VDHMM and Over
  35. Segmentation.
  36. Online Arabic Databases and Applications.
  37. Online Arabic Handwritten Words Recognition Based on HMM and Combination of Online and Offline Features.
  38. Part I: Pre
  39. Processing.
  40. An Assessment of Arabic Handwriting Recognition Technology.
  41. Layout Analysis of Arabic Script Documents.
  42. A Multi
  43. Stage Approach to Arabic Document Analysis.
  44. Pre
  45. Processing Issues in Arabic OCR.
  46. Segmentation of Ancient Arabic Documents.
  47. Features for HMM
  48. Based Arabic Handwritten Word Recognition Systems.
  49. Part II: Recognition.
  50. Printed Arabic Text Recognition.
  51. Handwritten Arabic Word Recognition Using the IFN/ENIT
  52. Database.
  53. RWTH OCR: A Large Vocabulary Optical Character Recognition System for Arabic Scripts.
  54. Arabic Handwriting Recognition using Bernoulli HMMs.
  55. Handwritten Farsi Words Recognition Using Hidden Markov Models.
  56. Offline Arabic Handwriting Recognition with Multidimensional Recurrent Neural Networks.
  57. Application of Fractal Theory in Farsi/Arabic Document Analysis.
  58. Multi
  59. Stream Markov Models for Arabic Handwriting Recognition.
  60. Towards Distributed Cursive Writing OCR Systems based on the Combination of Complementary Approaches.
  61. Part III: Evaluation.
  62. Data Collection and Annotation for Arabic Document Analysis.
  63. Arabic Handwriting Recognition Competitions.
  64. Benchmarking Strategy for Arabic Screen Rendered Word Recognition.
  65. Part IV: Applications.
  66. A Robust Word Spotting System for Historical Arabic Manuscripts.
  67. Arabic Text recognition using a Script
  68. Independent Methodology: A Unified HMM
  69. based Approach for Machine
  70. print and Handwritten Text.
  71. Arabic Handwriting Recognition Using VDHMM and Over
  72. Segmentation.
  73. Online Arabic Databases and Applications.
  74. Online Arabic Handwritten Words Recognition Based on HMM and Combination of Online and Offline Features.
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