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Cursive Script Text Recognition in Natural Scene Images

Arabic Text Complexities

  • Saad Bin Ahmed
  • Muhammad Imran Razzak
  • Rubiyah Yusof
Book

Table of contents

  1. Front Matter
    Pages i-xv
  2. Saad Bin Ahmed, Muhammad Imran Razzak, Rubiyah Yusof
    Pages 1-12
  3. Saad Bin Ahmed, Muhammad Imran Razzak, Rubiyah Yusof
    Pages 13-30
  4. Saad Bin Ahmed, Muhammad Imran Razzak, Rubiyah Yusof
    Pages 31-42
  5. Saad Bin Ahmed, Muhammad Imran Razzak, Rubiyah Yusof
    Pages 43-84
  6. Saad Bin Ahmed, Muhammad Imran Razzak, Rubiyah Yusof
    Pages 85-92
  7. Saad Bin Ahmed, Muhammad Imran Razzak, Rubiyah Yusof
    Pages 93-95
  8. Back Matter
    Pages 97-111

About this book

Introduction

This book offers a broad and structured overview of the state-of-the-art methods that could be applied for context-dependent languages like Arabic. It also provides guidelines on how to deal with Arabic scene data that appeared in an uncontrolled environment impacted by different font size, font styles, image resolution, and opacity of text.
 
Being an intrinsic script, Arabic and Arabic-like languages attract attention from research community. There are a number of challenges associated with the detection and recognition of Arabic text from natural images. This book discusses these challenges and open problems and also provides insights into the complexities and issues that researchers encounter in the context of Arabic or Arabic-like text recognition in natural and document images. It sheds light on fundamental questions, such as a) How the complexity of Arabic as a cursive scripts can be demonstrated b) What the structure of Arabic text is and how to consider the features from a given text and c) What guidelines should be followed to address the context learning ability of classifiers existing in machine learning.

Keywords

Cursive script Deep learning Arabic like Classifiers Context analysis Sequential learning

Authors and affiliations

  • Saad Bin Ahmed
    • 1
  • Muhammad Imran Razzak
    • 2
  • Rubiyah Yusof
    • 3
  1. 1.King Saud bin Abdulaziz University for Health SciencesRiyadhSaudi Arabia
  2. 2.School of Information TechnologyDeakin UniversityGeelongAustralia
  3. 3.Malaysia-Japan International Institute of Technology (M-JIIT)University of Technology MalaysiaKuala LumpurMalaysia

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-15-1297-1
  • Copyright Information Springer Nature Singapore Pte Ltd. 2020
  • Publisher Name Springer, Singapore
  • eBook Packages Computer Science
  • Print ISBN 978-981-15-1296-4
  • Online ISBN 978-981-15-1297-1
  • Buy this book on publisher's site