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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLII-2-643-2018</article-id>
<title-group>
<article-title>FEATURE MATCHING OF HISTORICAL IMAGES BASED ON GEOMETRY OF QUADRILATERALS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Maiwald</surname>
<given-names>F.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Schneider</surname>
<given-names>D.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Henze</surname>
<given-names>F.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Münster</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Niebling</surname>
<given-names>F.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Institute of Photogrammetry and Remote Sensing, TU Dresden, Germany</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Media Center, TU Dresden, Germany</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Human-Computer Interaction, Julius-Maximilians-Universität Würzburg, Germany</addr-line>
</aff>
<pub-date pub-type="epub">
<day>30</day>
<month>05</month>
<year>2018</year>
</pub-date>
<volume>XLII-2</volume>
<fpage>643</fpage>
<lpage>650</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2018 F. Maiwald et al.</copyright-statement>
<copyright-year>2018</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-2/643/2018/isprs-archives-XLII-2-643-2018.html">This article is available from https://isprs-archives.copernicus.org/articles/XLII-2/643/2018/isprs-archives-XLII-2-643-2018.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-2/643/2018/isprs-archives-XLII-2-643-2018.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-2/643/2018/isprs-archives-XLII-2-643-2018.pdf</self-uri>
<abstract>
<p>This contribution shows an approach to match historical images from the photo library of the Saxon State and University Library Dresden (SLUB) in the context of a historical three-dimensional city model of Dresden. In comparison to recent images, historical photography provides diverse factors which make an automatical image analysis (feature detection, feature matching and relative orientation of images) difficult. Due to e.g. film grain, dust particles or the digitalization process, historical images are often covered by noise interfering with the image signal needed for a robust feature matching. The presented approach uses quadrilaterals in image space as these are commonly available in man-made structures and façade images (windows, stones, claddings). It is explained how to generally detect quadrilaterals in images. Consequently, the properties of the quadrilaterals as well as the relationship to neighbouring quadrilaterals are used for the description and matching of feature points. The results show that most of the matches are robust and correct but still small in numbers.</p>
</abstract>
<counts><page-count count="8"/></counts>
</article-meta>
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