{"created":"2020-09-01T14:37:58.478107+00:00","id":4380,"links":{},"metadata":{"_buckets":{"deposit":"285325e3-7348-4675-9ca1-88328924873e"},"_deposit":{"id":"4380","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4380"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4380","sets":["1582963302567:1597824304333"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"A Robust Local Thresholding Method for Segmentation of Non-Uniform Coloured Documents","subitem_1551255648112":"en_US"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Text document segmentation is one of theessential steps text document recognition andextraction systems. The existing segmenting methodsare not much reliable for text with colour gradientand texture background. Also, long processing timeof existing methods is unfavorable.Thus, aiming to have reliable segmentationand less processing time, a new local thresholdingmethod is proposed in this study. The proposedmethod is based on pixel intensity magnificationconcept. Non-overlapping local window is used. Theperformance of proposed method is compared withthat of Otsu’s method and Niblack’s method. Theresults show that the proposed method give morereliable segmentation compared to Otus’ method, 1.2times longer processing time. Compared to Niblack’smethod, the segmented results are comparable andthe processing time is 5 times faster."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"segmentation"},{"interim":"local thresholding"},{"interim":"pixel magnification"},{"interim":"text document recognition"},{"interim":"character recognition"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-10-15"}],"displaytype":"preview","filename":"NJPSC 2019 Proceedings-pages-193-198.pdf","filesize":[{"value":"503 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4380/files/NJPSC 2019 Proceedings-pages-193-198.pdf"},"version_id":"3f0ee4f1-7ff0-42b7-9077-0c6e6896d43a"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"National Journal of Parallel and Soft Computing","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":"Aung, Thidar"},{"subitem_authors_fullname":"Thein, Thin Lai Lai"}]}]},"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":"2019-03"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/2317"},"item_title":"A Robust Local Thresholding Method for Segmentation of Non-Uniform Coloured Documents","item_type_id":"21","owner":"1","path":["1597824304333"],"publish_date":"2019-10-15","publish_status":"0","recid":"4380","relation_version_is_last":true,"title":["A Robust Local Thresholding Method for Segmentation of Non-Uniform Coloured Documents"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2022-03-24T23:12:11.208026+00:00"}