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          <dc:title>P2-invariant を用いた文書画像検索</dc:title>
          <dc:title xml:lang="en">Document image retrieval using P2-invariant</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>大西, 友貴</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>小山田, 雄仁</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>三柴, 数</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>近藤, 克哉</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Tomotaka, Ohnishi</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Yuji, Oyamada</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Kazu, Mishiba</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Katsuya, Kondo</jpcoar:creatorName>
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          <datacite:description descriptionType="Other">文書画像検索とはカメラで撮影した文書画像を事前に用意したデータベース中から見つける手法を指す．従来法では，射影不変だが点の順列に対して暖昧性を持つ特徴量を用いていた．そのため順列に対し暖昧性を解決する工夫が行われてきたが，特徴量に冗長性を持たせるため本質的な解決策とは言えなかった．本論文では射影不変かつ置換不変な特徴量を用いることで，冗長性を解消した文書画像検索を提案する．実験では，シミュレーション・実画像実験を行い，本手法の性能を検証した．</datacite:description>
          <datacite:description descriptionType="Other">Given an image capturing a document, document image retrieval finds the closest image from a document image database. Typical solutions regard each word as a point and solve the retrieval as points-to-points matching. Locally Likely Arrangement Hashing (LLAH) uses affine/perspective invariants as feature and achieves real-time retrieval system based on hashing. LLAH contains a redundancy to solve the permutation ambiguity of points detected from an image. In this paper, we propose to introduce P2-invariant, perspective and permutation invariant, as feature for document image retrieval. Contrast to the existing methods, the proposed method solves the retrieval problem by 5-tuple-to-5-tuple matching technique. The experimental result shows the performance of the proposed method.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2016-08-29</datacite:date>
          <dc:language>jpn</dc:language>
          <dc:type rdf:resource="http://purl.org/coar/resource_type/c_18gh">technical report</dc:type>
          <jpcoar:identifier identifierType="URI">https://ipsj.ixsq.nii.ac.jp/records/174412</jpcoar:identifier>
          <jpcoar:sourceIdentifier identifierType="ISSN">2188-8701</jpcoar:sourceIdentifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AA11131797</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>研究報告コンピュータビジョンとイメージメディア（CVIM）</jpcoar:sourceTitle>
          <jpcoar:volume>2016-CVIM-203</jpcoar:volume>
          <jpcoar:issue>3</jpcoar:issue>
          <jpcoar:pageStart>1</jpcoar:pageStart>
          <jpcoar:pageEnd>6</jpcoar:pageEnd>
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