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        <identifier>oai:jin-ai.repo.nii.ac.jp:00001062</identifier>
        <datestamp>2023-06-20T16:11:40Z</datestamp>
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          <dc:title>アルファベット指文字の肌色抽出と認識に関する基礎的研究</dc:title>
          <dc:title xml:lang="en">Experimental Analysis of Skin Color Detection and Automated Recognition for Finger Spelling</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>島田, 貢明</jpcoar:creatorName>
            <jpcoar:creatorName xml:lang="ja-Kana">シマダ, ミツアキ</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Shimada, Mitsuaki</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:subject subjectScheme="Other">指文字</jpcoar:subject>
          <jpcoar:subject subjectScheme="Other">手話</jpcoar:subject>
          <jpcoar:subject subjectScheme="Other">肌色抽出</jpcoar:subject>
          <jpcoar:subject subjectScheme="Other">画像処理</jpcoar:subject>
          <jpcoar:subject subjectScheme="Other">画像認識</jpcoar:subject>
          <jpcoar:subject subjectScheme="Other">ニューラルネットワーク</jpcoar:subject>
          <jpcoar:subject xml:lang="en" subjectScheme="Other">finger spelling</jpcoar:subject>
          <jpcoar:subject xml:lang="en" subjectScheme="Other">sign language</jpcoar:subject>
          <jpcoar:subject xml:lang="en" subjectScheme="Other">skin color detection</jpcoar:subject>
          <jpcoar:subject xml:lang="en" subjectScheme="Other">image processing</jpcoar:subject>
          <jpcoar:subject xml:lang="en" subjectScheme="Other">image recognition</jpcoar:subject>
          <jpcoar:subject xml:lang="en" subjectScheme="Other">neural network</jpcoar:subject>
          <datacite:description descriptionType="Abstract">This research is concerned with automated recognition of sign language. In this paper, new algorithm using Neural Network which recognizes finger spelled word of American Sign Language (ASL) is proposed.Experiment is also conducted using actual video of finger spelled words. This is a challenging task since the ASL alphabets are expressed by the various figure of one hand. The captured input image in RGB is converted to HSV color space, because it is more related to human color perception. Automated recognition experiment using proposed algorithm is done to 26 characters of ASL finger spelling. According to the result of experimental analysis, it is proved that the algorithm proposed in this paper is effective in finger spelling recognition.</datacite:description>
          <dc:publisher>仁愛女子短期大学</dc:publisher>
          <datacite:date dateType="Issued">2011-03-31</datacite:date>
          <dc:language>jpn</dc:language>
          <dc:type rdf:resource="http://purl.org/coar/resource_type/c_6501">departmental bulletin paper</dc:type>
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          <jpcoar:identifier identifierType="DOI">https://doi.org/10.57426/00001056</jpcoar:identifier>
          <jpcoar:identifier identifierType="URI">https://jin-ai.repo.nii.ac.jp/records/1062</jpcoar:identifier>
          <jpcoar:identifierRegistration identifierType="JaLC">10.57426/00001056</jpcoar:identifierRegistration>
          <jpcoar:sourceIdentifier identifierType="ISSN">09138587</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>仁愛女子短期大学研究紀要</jpcoar:sourceTitle>
          <jpcoar:issue>43</jpcoar:issue>
          <jpcoar:pageStart>1</jpcoar:pageStart>
          <jpcoar:pageEnd>6</jpcoar:pageEnd>
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            <datacite:date dateType="Available">2022-10-27</datacite:date>
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