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          <dc:title>ピクトグラムマッチングのための輪郭情報を取り入れた局所形状記述子</dc:title>
          <dc:title xml:lang="en">Local Shape Descriptor with Contour Information for Pictogram Matching</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>上西, くるみ</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName>青木, 輝勝</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Kurumi, Kaminishi</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Terumasa, Aoki</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:subject subjectScheme="Other">一般セッション2</jpcoar:subject>
          <datacite:description descriptionType="Other">標識など身近に多く存在しているピクトグラム （単純な絵記号） のマッチングには広く実用的な応用が考えられる．しかし，既存の自然画像マッチング技術では単純な画像の認識は大変難しく，撮影条件の変化はそれをさらに困難にしている．本稿では，この問題を解決するために，輪郭と凸包の関係を用いた撮影条件の変化に頑強な局所形状記述子を提案する．局所特徴量にすることで撮影条件の変化に柔軟な形状記述子とし，輪郭と凸包の関係を用いることによって個々のピクトグラム独自の特徴量記述を可能にした．提案方式は，既存手法と比較してピクトグラムのマッチ率，計算時間をともに大幅に向上させるものである．</datacite:description>
          <datacite:description descriptionType="Other">Pictogram, which is a simple picture-based symbol, is widely used to indicate important facilities (such as “rest room”) or important rules (such as “no smoking”). A lot of new application will be generated if a practicable pictogram matching method is generated. Unfortunately current natural image matching methods are not suited for this purpose because pictogram contains less information than natural images. Furthermore, the matching results strongly depend on photographing conditions. In this paper, we present a novel pictogram matching method which is robust to the changes of photographing conditions. Our method uses relationship between contour and convex hull, and extracts local features from a pictogram to represent shape descriptors. The experiments show our method improves the matching rate and computation time for existing methods.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2017-01-12</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/176602</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>2017-CVIM-205</jpcoar:volume>
          <jpcoar:issue>5</jpcoar:issue>
          <jpcoar:pageStart>1</jpcoar:pageStart>
          <jpcoar:pageEnd>8</jpcoar:pageEnd>
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            <datacite:date dateType="Available">2019-01-12</datacite:date>
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