{"created":"2025-01-18T22:45:03.412290+00:00","updated":"2025-01-23T03:04:52.922487+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00009991","sets":["581:599:609"]},"path":["609"],"owner":"1","recid":"9991","title":["ベクタ画像を対象としたプリミティブ選択モデルに基づくオブジェクト領域抽出"],"pubdate":{"attribute_name":"公開日","attribute_value":"2007-03-15"},"_buckets":{"deposit":"6a285d96-88e2-47b2-8956-b1866e1050d0"},"_deposit":{"id":"9991","pid":{"type":"depid","value":"9991","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"ベクタ画像を対象としたプリミティブ選択モデルに基づくオブジェクト領域抽出","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ベクタ画像を対象としたプリミティブ選択モデルに基づくオブジェクト領域抽出"},{"subitem_title":"Object Extraction for Vector Images with Primitive Selection Model","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"特集：インタラクション技術の原理と応用","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2007-03-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"電気通信大学"},{"subitem_text_value":"電気通信大学"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"The University of Electro-Communications","subitem_text_language":"en"},{"subitem_text_value":"The University of Electro-Communications","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/9991/files/IPSJ-JNL4803019.pdf"},"date":[{"dateType":"Available","dateValue":"2009-03-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL4803019.pdf","filesize":[{"value":"778.1 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"57a0e4fc-2080-4bdd-bc2d-8972c0763021","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2007 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"林, 貴宏"},{"creatorName":"尾内, 理紀夫"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Takahiro, Hayashi","creatorNameLang":"en"},{"creatorName":"Rikio, Onai","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_2_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_2_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7764","subitem_source_identifier_type":"ISSN"}]},"item_2_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本論文では，2D ベクタ画像を対象とするオブジェクト領域抽出法を提案，評価する．ラスタ画像からオブジェクト領域を自動抽出する手法はこれまで提案されてきたが，ベクタ画像を対象とした手法は報告されていない．そのため，既存手法によりベクタ画像からオブジェクト領域を抽出するためには，ベクタ画像をいったんラスタ化する必要があった．しかし，ラスタ化によってベクタ画像が持つ様々な利点は失われる．そこで本研究は，ベクタ画像の利点を活用できる効率的なオブジェクト領域抽出法を提案した．提案手法は，ベクタ画像を構成する個々の図形要素と，これら図形要素が定義しているベクタ画像中の部分領域との関係を解析し，オブジェクト領域を構成している図形要素群を判別する．評価実験として，提案手法と従来のラスタベース手法の1 つであるACM（Active Contour Model）の抽出精度と速度性能を比較した．実験結果から，提案手法がACM よりも高い抽出精度と速度性能を持つことを確認した．また，提案手法の速度性能に改善の余地があることを確認した．","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"This paper presents a novel object extraction from 2D vector images. Although various object extractions from raster images have been proposed, none of them has a mechanism for handling vector images. Therefore, in order to extract object regions from vector images using previous methods, it is necessary to convert vector images into raster images. However, various mertis of vector image are discared by rasterization. In this study, we have proposed a novel object extraction method using merits of vector images. The proposed method analyzes relations between individual primitives of vector images and the regions defined by these primitives. Accoring to the analysis, a set of primitives defining object region is detected. We have compared accuracy and speed performance between the proposed method and ACM (Active Contour Model), which is a traditional raster-based object extraction method. Experimental results have shown that the proposed method has higher accuracy and speed performance than ACM. In addition, we have confirmed the proposed method has room for improvement in speed performance.","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1165","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicPageStart":"1154","bibliographicIssueDates":{"bibliographicIssueDate":"2007-03-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"3","bibliographicVolumeNumber":"48"}]},"relation_version_is_last":true,"item_2_alternative_title_2":{"attribute_name":"その他タイトル","attribute_value_mlt":[{"subitem_alternative_title":"画像処理"}]},"weko_creator_id":"1"},"id":9991,"links":{}}