{"_buckets": {"deposit": "6f7d3786-2929-4509-9555-7ecd892b4846"}, "_deposit": {"id": "4249", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4249"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4249", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Optical Character Recognition System For Myanmar Printed Documents", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Automatic machine-printed OpticalCharacters or texts Recognizers (OCR) arehighly desirable for a multitude of modern ITapplications, including Digital Library software.However, the state of the art OCR systems can’tdo for Myanmar scripts as our language posemany challenges for document understanding.Therefore, we design an Optical CharacterRecognition System for Myanmar PrintedDocument (OCRMPD), with several proposetechniques that can automatically recognizeMyanmar printed text from document image. Inorder to get more accuracy system, we proposethe method for isolation of the character imageby using not only the projection methods but alsostructural analysis for wrongly segmentedcharacters. To reveal the effectiveness of oursegmentation technique, we follow a new hybridfeature extraction method and choose the SVMclassifier for recognition of the character image.The proposed algorithms have been tested on avariety of Myanmar printed documents and theresults of the experiments indicate that themethods can increase the segmentation accuracyas well as recognition rates."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value": []}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-03"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "9062.pdf", "filesize": [{"value": "531 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 531000.0, "url": {"url": "https://meral.edu.mm/record/4249/files/9062.pdf"}, "version_id": "c12b1ae9-d40a-4266-8b1b-2a58c227bd84"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Ninth International Conference On Computer Applications (ICCA 2011)", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Win, Htwe Pa Pa"}, {"subitem_authors_fullname": "Tun, Khin Nwe Ni"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2011-05-05"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/204"}, "item_title": "Optical Character Recognition System For Myanmar Printed Documents", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004249", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-03"}, "publish_date": "2019-07-03", "publish_status": "0", "recid": "4249", "relation": {}, "relation_version_is_last": true, "title": ["Optical Character Recognition System For Myanmar Printed Documents"], "weko_shared_id": -1}