Cover Image

Hybrid model of post-processing techniques for Arabic optical character recognition

Optical character recognition (OCR) is used to extract text contained in an image. One of the stages in OCR is the post-processing and it corrects the errors of OCR output text. The OCR multiple outputs approach consists of three processes: differentiation, alignment, and voting. Existing differenti...

Full description

Saved in:
Bibliographic Details
Main Author: Habeeb, Imad Qasim
Format: Thesis
Language:English
English
Published: 2016
Subjects:
T58.5-58.64 Information technology
QA75 Electronic computers. Computer science
Online Access:http://etd.uum.edu.my/6030/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uum.etd.6030
record_format eprints
spelling my.uum.etd.60302021-04-05T02:28:59Z http://etd.uum.edu.my/6030/ Hybrid model of post-processing techniques for Arabic optical character recognition Habeeb, Imad Qasim T58.5-58.64 Information technology QA75 Electronic computers. Computer science Optical character recognition (OCR) is used to extract text contained in an image. One of the stages in OCR is the post-processing and it corrects the errors of OCR output text. The OCR multiple outputs approach consists of three processes: differentiation, alignment, and voting. Existing differentiation techniques suffer from the loss of important features as it uses N-versions of input images. On the other hand, alignment techniques in the literatures are based on approximation while the voting process is not context-aware. These drawbacks lead to a high error rate in OCR. This research proposed three improved techniques of differentiation, alignment, and voting to overcome the identified drawbacks. These techniques were later combined into a hybrid model that can recognize the optical characters in the Arabic language. Each of the proposed technique was separately evaluated against three other relevant existing techniques. The performance measurements used in this study were Word Error Rate (WER), Character Error Rate (CER), and Non-word Error Rate (NWER). Experimental results showed a relative decrease in error rate on all measurements for the evaluated techniques. Similarly, the hybrid model also obtained lower WER, CER, and NWER by 30.35%, 52.42%, and 47.86% respectively when compared to the three relevant existing models. This study contributes to the OCR domain as the proposed hybrid model of post-processing techniques could facilitate the automatic recognition of Arabic text. Hence, it will lead to a better information retrieval. 2016 Thesis NonPeerReviewed text en /6030/1/s94758_01.pdf text en /6030/2/s94758_02.pdf Habeeb, Imad Qasim (2016) Hybrid model of post-processing techniques for Arabic optical character recognition. PhD. thesis, Universiti Utara Malaysia.
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Electronic Theses
url_provider http://etd.uum.edu.my/
language English
English
topic T58.5-58.64 Information technology
QA75 Electronic computers. Computer science
spellingShingle T58.5-58.64 Information technology
QA75 Electronic computers. Computer science
Habeeb, Imad Qasim
Hybrid model of post-processing techniques for Arabic optical character recognition
description Optical character recognition (OCR) is used to extract text contained in an image. One of the stages in OCR is the post-processing and it corrects the errors of OCR output text. The OCR multiple outputs approach consists of three processes: differentiation, alignment, and voting. Existing differentiation techniques suffer from the loss of important features as it uses N-versions of input images. On the other hand, alignment techniques in the literatures are based on approximation while the voting process is not context-aware. These drawbacks lead to a high error rate in OCR. This research proposed three improved techniques of differentiation, alignment, and voting to overcome the identified drawbacks. These techniques were later combined into a hybrid model that can recognize the optical characters in the Arabic language. Each of the proposed technique was separately evaluated against three other relevant existing techniques. The performance measurements used in this study were Word Error Rate (WER), Character Error Rate (CER), and Non-word Error Rate (NWER). Experimental results showed a relative decrease in error rate on all measurements for the evaluated techniques. Similarly, the hybrid model also obtained lower WER, CER, and NWER by 30.35%, 52.42%, and 47.86% respectively when compared to the three relevant existing models. This study contributes to the OCR domain as the proposed hybrid model of post-processing techniques could facilitate the automatic recognition of Arabic text. Hence, it will lead to a better information retrieval.
format Thesis
author Habeeb, Imad Qasim
author_facet Habeeb, Imad Qasim
author_sort Habeeb, Imad Qasim
title Hybrid model of post-processing techniques for Arabic optical character recognition
title_short Hybrid model of post-processing techniques for Arabic optical character recognition
title_full Hybrid model of post-processing techniques for Arabic optical character recognition
title_fullStr Hybrid model of post-processing techniques for Arabic optical character recognition
title_full_unstemmed Hybrid model of post-processing techniques for Arabic optical character recognition
title_sort hybrid model of post-processing techniques for arabic optical character recognition
publishDate 2016
url http://etd.uum.edu.my/6030/
_version_ 1696978305883832320
score 13.211869

Similar Items