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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-XLIV-4-W1-2020-49-2020</article-id>
<title-group>
<article-title>POINT CLOUD ROOM SEGMENTATION BASED ON INDOOR SPACES AND 3D MATHEMATICAL MORPHOLOGY</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Frías</surname>
<given-names>E.</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>Balado</surname>
<given-names>J.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Díaz-Vilariño</surname>
<given-names>L.</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>Lorenzo</surname>
<given-names>H.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Universidade de Vigo, CINTECX, Applied Geotechnologies Research Group, Campus universitario de Vigo, As Lagoas, Marcosende 36310 Vigo, Spain</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Delft University of Technology, Faculty of Architecture and the Built Environment, GIS Technology Section, 2628 BL Delft, the Netherlands</addr-line>
</aff>
<pub-date pub-type="epub">
<day>03</day>
<month>09</month>
<year>2020</year>
</pub-date>
<volume>XLIV-4/W1-2020</volume>
<fpage>49</fpage>
<lpage>55</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2020 E. Frías et al.</copyright-statement>
<copyright-year>2020</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/XLIV-4-W1-2020/49/2020/isprs-archives-XLIV-4-W1-2020-49-2020.html">This article is available from https://isprs-archives.copernicus.org/articles/XLIV-4-W1-2020/49/2020/isprs-archives-XLIV-4-W1-2020-49-2020.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLIV-4-W1-2020/49/2020/isprs-archives-XLIV-4-W1-2020-49-2020.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLIV-4-W1-2020/49/2020/isprs-archives-XLIV-4-W1-2020-49-2020.pdf</self-uri>
<abstract>
<p>Room segmentation is a matter of ongoing interesting for indoor navigation and reconstruction in robotics and AEC. While in robotics field, the problem room segmentation has been typically addressed on 2D floorplan, interest in enrichment 3D models providing more detailed representation of indoors has been growing in the AEC. Point clouds make available more realistic and update but room segmentation from point clouds is still a challenging topic. This work presents a method to carried out point cloud segmentation into rooms based on 3D mathematical morphological operations. First, the input point cloud is voxelized and indoor empty voxels are extracted by CropHull algorithm. Then, a morphological erosion is performed on the 3D image of indoor empty voxels in order to break connectivity between voxels belonging to adjacent rooms. Remaining voxels after erosion are clustered by a 3D connected components algorithm so that each room is individualized. Room morphology is retrieved by individual 3D morphological dilation on clustered voxels. Finally, unlabelled occupied voxels are classified according proximity to labelled empty voxels after dilation operation. The method was tested in two real cases and segmentation performance was evaluated with encouraging results.</p>
</abstract>
<counts><page-count count="7"/></counts>
</article-meta>
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