{"_buckets": {"deposit": "39db249e-29d4-4869-9d27-a5b51c01a70e"}, "_deposit": {"id": "4544", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4544"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4544", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Robust Local Thresholding Method for Segmentation of Non-Uniform Coloured Documents", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Text document segmentation is one of the essential steps in text documentrecognition and extraction systems. The existing image segmentation methods are notmuch reliable for text with colour gradient and texture background. Also, longprocessing time of existing methods is unfavorable. Thus, aiming to have reliablesegmentation and less processing time, a new local thresholding method is proposedand its performance is tested in this study.The proposed method is based on pixel intensity magnification concept. Inproposed algorithm, the input image is enhanced by edge sharpening. Then, the imageis divided into multiple local windows by using non-overlapping. The magnificationfactor for each non-overlapping local window is calculated based on minimumintensity, maximum intensity, range and the number of dominant intensities in thecorresponding local window. For segmenting pixels in each local window,magnification factor is used.The performance of proposed algorithm is measured in terms of segmentingaccuracy and processing time. The tested images include different types such as textin uniform colour, text in multicolour, text in gradient background, text in national ID,text with watermark, highlight text, text in light illumination, text in passport, text inbank card. Also, the performances of Otus’ and Niblack’s methods are tested with thesame images.The proposed method gives the better results for most images with maximumaccuracy of 100% and lowest accuracy of 80%. The highest efficiency of Otsu’smethod is 100% and its lowest accuracy is 0%. Since Otsu’s method loses all datasometimes. For Niblack’s method, it gives 100% accuracy only for text with simplecolour background while its lowest accuracy is 10%. The proposed system’s averageaccuracy is higher than Otus’ and Niblack’s average accuracy."}]}, "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": "2020-01-03"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Thidar Aung.pdf", "filesize": [{"value": "3509 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 3509000.0, "url": {"url": "https://meral.edu.mm/record/4544/files/Thidar Aung.pdf"}, "version_id": "ff0a4987-665f-47b3-9501-6200ac910cc8"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "", "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": "University of Computer Studies, Yangon", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Aung, Thidar"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Thesis"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2019-08"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/2467"}, "item_title": "Robust Local Thresholding Method for Segmentation of Non-Uniform Coloured Documents", "item_type_id": "21", "owner": "1", "path": ["1597824322519"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004544", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-01-03"}, "publish_date": "2020-01-03", "publish_status": "0", "recid": "4544", "relation": {}, "relation_version_is_last": true, "title": ["Robust Local Thresholding Method for Segmentation of Non-Uniform Coloured Documents"], "weko_shared_id": -1}