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...
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| Format: | Thesis |
| Language: | en en |
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2016
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| Online Access: | https://etd.uum.edu.my/6030/1/s94758_01.pdf https://etd.uum.edu.my/6030/2/s94758_02.pdf https://etd.uum.edu.my/6030/ |
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| author | Habeeb, Imad Qasim |
| author_facet | Habeeb, Imad Qasim |
| author_sort | Habeeb, Imad Qasim |
| building | UUM Library |
| collection | Institutional Repository |
| content_provider | Universiti Utara Malaysia |
| content_source | UUM Electronic Theses |
| continent | Asia |
| country | Malaysia |
| 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 |
| id | my.uum.etd-6030 |
| institution | Universiti Utara Malaysia |
| language | en en |
| publishDate | 2016 |
| record_format | eprints |
| spelling | my.uum.etd-60302021-04-05T02:28:59Z https://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 https://etd.uum.edu.my/6030/1/s94758_01.pdf text en https://etd.uum.edu.my/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. |
| 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 |
| title | 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_short | Hybrid model of post-processing techniques for Arabic optical character recognition |
| title_sort | hybrid model of post-processing techniques for arabic optical character recognition |
| topic | T58.5-58.64 Information technology QA75 Electronic computers. Computer science |
| url | https://etd.uum.edu.my/6030/1/s94758_01.pdf https://etd.uum.edu.my/6030/2/s94758_02.pdf https://etd.uum.edu.my/6030/ |
| url_provider | http://etd.uum.edu.my/ |