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Title of Thesis

Online Urdu Character Recognition In Unconstrained Environment

Author(s)

Muhammad Imran Razzak

Institute/University/Department Details
Department of Computer Science, Faculty of Basic And Applied Sciences / International Islamic University, Islamabad
Session
2011
Subject
Computer Science
Number of Pages
241
Keywords (Extracted from title, table of contents and abstract of thesis)
Technology, Urdu, Unconstrained, Ghost, Character, Environment, Logics, Visual, Online, Concept, Recognition, Script, Arabic, Classification

Abstract
Computer, the humongous giant of technology, has brought innovative changes in every aspect of life, especially in applications imitating humans.Currently, it is used in every field of life to facilitate human endeavor.One such application is character recognition. Character recognition is an important offshoot of pattern recognition problems. It imitates a human’s ability to read, using a machine.It has been a field of intensive, if exotic, research since the early days of the computer.This task becomes more complex and demanding in case of handwritten and cursive text.Arabic script-based languages, which are used by almost a quarter of the world’s population [Belaid et. al, 2010], are cursive, rich in diacritical marks and variety of writing styles present a challenging task for the researchers.Urdu is an Arabic script based languages however the Urdu character set is the superset of all Arabic script-based languages.Character recognition has been performed either through segmentation free or segmentation based approaches.There are numerous issues with a segmentation free approach, and it is very difficult to train using a large dataset.On the other hand in Urdu, a segmentation based approach has a large overhead and has less accuracy for cursive script as compared to segmentation free methods.In terms of classification, this thesis presents two approaches for Urdu character recognition: segmentation free method based on a hybrid approach (HMM and fuzzy logic), and bio-inspired character recognition system that uses fuzzy logics. Fuzzy is used as inner and outer shells for preprocessing and post processing of HMM. Biologically inspired multilayered fuzzy rules based system has been presented.Using the human visual concept, a layered approach has been suggested where the diacritical marks are separated from the ghost characters and mapped onto the primary ligature in the final layer.The proposed technique also caters to Multilanguage character recognition system for all Arabic script-based languages like Arabic, Persian, Urdu, Punjabi etc.The presented multilayered bio-inspired approach recognizes the ligature by extracting the features and combining them to find new premises in a bottom up fashion and it provided accuracy of 87.4%.

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3,771 KB
S. No. Chapter Title of the Chapters Page Size (KB)
1 0 CONTENTS

 

vii
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2

1

INTRODUCTION

1.1 Motivation
1.2 Classification of Character Recognition
1.3 Constrained Vs Unconstrained
1.4 Urdu/Arabic Character Recognition Process
1.5 Challenges to Urdu Script Character Recognition
1.6 Objectives
1.7 Knowledge Based Urdu Character Recognition System (research methodlogy)
1.8 Contributions
1.9 Thesis Organization

1
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3 2 HANDWRITTEN CHARACTER RECOGNITION: LITERATURE SURVEY

2.1 Preprocessing
2.2 Feature Extraction
2.3 Classifier
2.4 Final Remarks

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4 3 BACKGROUND KNOWLEDGE

3.1 Fuzzy Logics
3.2 Human Visual Perception
3.3 Bio-Inspired Image Processing
3.4 Bio-Inspired Fuzzy Logics System
3.5 Final Remarks

45
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5 4 GHOST CHARACTER RECOGNITION THEORY

4.1 Urdu Script Based Languages
4.2 Arabic Script Based Languages Character Recognition
4.3 Ghost Character Theory
4.4 Ghost Character Recognition Theory
4.5 Effect of Ghost Character Theory
4.6 Merits
4.7 Demerits
4.8 Final Remarks

61
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6 5 BIO-INSPIRED FUZZY BASED PREPROCESSING AND FEATURE EXTRACTION

5.1 Preprocessing Methodology
5.2 Feature Extraction
5.3 Final Remarks

78
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7 6 BIOLOGICAL INSPIRED URDU CHARACTER RECOGNITION

6.1 Multilayered Human Visual System
6.2 Multilayered Character Recognition
6.3 Discussion
6.4 Final Remarks

137
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8 7 HOLISTIC APPROACH FOR URDU CHARACTER RECOGNITION USING MODIFIED HMM

7.1 Modified HMM Based Urdu Classification
7.2 HMM And Fuzzy Logics: A Hybrid Approach
7.3 Post Processing
7.4 Final Remarks

116
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9 8 COMPRATIVE ANALYSIS AND CONCLUSIONS

8.1 Ghost Character Recognition Theory
8.2 Segmentation Free and Segmentation Approach
8.3 Conclusions
8.4 Future Work

162
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10

9

REFERENCES AND APPENDIX

 

176
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