{"created":"2025-01-18T23:17:14.174211+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00053048","sets":["1164:4619:4682:4685"]},"path":["4685"],"owner":"1","recid":"53048","title":["尺度空間法による中心線の抽出：尺度空間の特徴量の逆変換とその統合"],"pubdate":{"attribute_name":"公開日","attribute_value":"1998-05-27"},"_buckets":{"deposit":"4a579938-c515-4132-9209-f668c0053899"},"_deposit":{"id":"53048","pid":{"type":"depid","value":"53048","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"尺度空間法による中心線の抽出：尺度空間の特徴量の逆変換とその統合","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"尺度空間法による中心線の抽出：尺度空間の特徴量の逆変換とその統合"},{"subitem_title":"Central Axes Extraction by Linear Scale - Space Analysis : Inverse Mapping of Features in the Scale Space","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"1998-05-27","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"千葉大学情報画像工学科"},{"subitem_text_value":"千葉大学情報画像工学科"},{"subitem_text_value":"千葉大学情報画像工学科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Dept. of Information and Images Sciences, Chiba University","subitem_text_language":"en"},{"subitem_text_value":"Dept. of Information and Images Sciences, Chiba University","subitem_text_language":"en"},{"subitem_text_value":"Dept. of Information and Images Sciences, Chiba University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"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/53048/files/IPSJ-CVIM98111009.pdf"},"date":[{"dateType":"Available","dateValue":"2000-05-27"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM98111009.pdf","filesize":[{"value":"842.5 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":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"750361e2-d151-4d88-8c81-c9611b50a647","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 1998 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"井宮, 淳"},{"creatorName":"勝田, 亮"},{"creatorName":"市川, 薫"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Atsushi, Imiya","creatorNameLang":"en"},{"creatorName":"Ryo, Katsuta","creatorNameLang":"en"},{"creatorName":"Akira, Ichikawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"尺度空間解析は，視覚の物理モデルから生まれたものであり，実際の人間の視覚モデルと関係があるであろうことが指摘されている．D.MarrはDGF(Difference of Gauss Function)による画像中のエッジ抽出モデルに関して数理モデルと人間の認知モデルとの相関性を，認知科学の立場から詳細に検討した．本研究では，尺度空間の中に新たな停留点集合として構造線を導入する．さらに，最適尺度での構造線をノードの記号として持つ構造線木を導入する．この構造線木によって，濃淡画像に対して画像の部分中心線を定義する．さらに，部分中心線を構造線木の示す位相構造にしたがって統合した平面上の線画として濃淡画像の中心線を定義する．そして，提案する手法によって抽出した中心線が，人間の認知モデルを説明するものかを確認する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In this paper we introduce a method for the extraction of central axes of gray-scale images using the scale-space framework. We fitst define a class of stationary points in the linear scale-space using the structure lines of gray-scale images. Second, we define the central axis of a gray-scale image as the unification of the local axes which are obtained in view fields. We define the central axes, which are typical features of images in low level vision, using the theory of view fields, which is a protocol from intermediate vision to high level vision. This property implies that for the accurate extraction of low level features, it is necessary to combine both bottom-up and top-down operations among low level vision, intermediate vision and high level vision in computational vision. The numerical results show that our algorithm extracts central axes which are very similar to central axes which human being fells. Psychological experiments conclude that for images with high contrast in gray scale, if the scaling of images is large, the extracted features have correlations to these extracted by hyman being.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"72","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"65","bibliographicIssueDates":{"bibliographicIssueDate":"1998-05-27","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"46(1998-CVIM-111)","bibliographicVolumeNumber":"1998"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"id":53048,"updated":"2025-01-22T06:30:06.506444+00:00","links":{}}