Dataset Open Access

MSBin - MultiSpectral Document Binarization

Hollaus Fabian; Brenner Simon; Sablatnig Robert


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  <identifier identifierType="DOI">10.5281/zenodo.3257366</identifier>
  <creators>
    <creator>
      <creatorName>Hollaus Fabian</creatorName>
      <affiliation>Computer Vision Lab, TU Wien</affiliation>
    </creator>
    <creator>
      <creatorName>Brenner Simon</creatorName>
      <affiliation>Computer Vision Lab, TU Wien</affiliation>
    </creator>
    <creator>
      <creatorName>Sablatnig Robert</creatorName>
      <affiliation>Computer Vision Lab, TU Wien</affiliation>
    </creator>
  </creators>
  <titles>
    <title>MSBin - MultiSpectral Document Binarization</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <dates>
    <date dateType="Issued">2019-06-27</date>
  </dates>
  <resourceType resourceTypeGeneral="Dataset"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3257366</alternateIdentifier>
  </alternateIdentifiers>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3257365</relatedIdentifier>
    <relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/cvl</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;This dataset is named &lt;em&gt;MSBin&lt;/em&gt; which stands for MultiSpectral Document Binarization. The dataset is dedicated to the (document image) binarization of multispectral images. A ReadMe is contained within the dataset and also available here:&lt;br&gt;
&lt;a href="https://gist.github.com/hollaus/340acab1d6f25b181eefd0251b295c80"&gt;ReadMe&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;The dataset is introduced in:&lt;br&gt;
Hollaus, S. Brenner and R. Sablatnig: &amp;quot;CNN based Binarization of MultiSpectral Document Images&amp;quot;. To appear in: International Conference on Document Analysis and Recognition (ICDAR), 2019.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/674943/">674943</awardNumber>
      <awardTitle>Recognition and Enrichment of Archival Documents</awardTitle>
    </fundingReference>
    <fundingReference>
      <funderName>Austrian Science Fund</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100002428</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/FWF/Einzelprojekte/P+29892/">P 29892</awardNumber>
      <awardTitle>The Origin of the Glagolitic-Old Church Slavonic Manuscripts</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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