A Visual Framework for Digital Reconstruction of Topographic Maps

Handle URI:
http://hdl.handle.net/10754/332722
Title:
A Visual Framework for Digital Reconstruction of Topographic Maps
Authors:
Thabet, Ali Kassem ( 0000-0001-7513-0748 ) ; Smith, Neil; Wittmann, Roland; Schneider, Jens
Abstract:
We present a framework for reconstructing Digital Elevation Maps (DEM) from scanned topographic maps. We first rectify the images to ensure that maps fit together without distortion. To segment iso-contours, we have developed a novel semi-automated method based on mean-shifts that requires only minimal user interaction. Contour labels are automatically read using an OCR module. To reconstruct the output DEM from scattered data, we generalize natural neighbor interpolation to handle the transfinite case (contours and points). To this end, we use parallel vector propagation to compute a discrete Voronoi diagram of the constraints, and a modified floodfill to compute virtual Voronoi tiles. Our framework is able to handle tens of thousands of contours and points and can generate DEMs comprising more than 100 million samples. We provide quantitative comparison to commercial software and show the benefits of our approach. We furthermore show the robustness of our method on a massive set of old maps predating satellite acquisition. Compared to other methods, our framework is able to accurately and efficiently generate a final DEM despite inconsistencies, sparse or missing contours even for highly complex and cluttered maps. Therefore, this method has broad applicability for digitization and reconstruction of the world's old topographic maps that are often the only record of past landscapess and cultural heritage before their destruction under modern development.
KAUST Department:
Visual Computing Center (VCC)
Issue Date:
30-Sep-2014
Type:
Technical Report
Appears in Collections:
Technical Reports; Visual Computing Center (VCC)

Full metadata record

DC FieldValue Language
dc.contributor.authorThabet, Ali Kassemen
dc.contributor.authorSmith, Neilen
dc.contributor.authorWittmann, Rolanden
dc.contributor.authorSchneider, Jensen
dc.date.accessioned2014-10-12T08:14:15Z-
dc.date.available2014-10-12T08:14:15Z-
dc.date.issued2014-09-30en
dc.identifier.urihttp://hdl.handle.net/10754/332722en
dc.description.abstractWe present a framework for reconstructing Digital Elevation Maps (DEM) from scanned topographic maps. We first rectify the images to ensure that maps fit together without distortion. To segment iso-contours, we have developed a novel semi-automated method based on mean-shifts that requires only minimal user interaction. Contour labels are automatically read using an OCR module. To reconstruct the output DEM from scattered data, we generalize natural neighbor interpolation to handle the transfinite case (contours and points). To this end, we use parallel vector propagation to compute a discrete Voronoi diagram of the constraints, and a modified floodfill to compute virtual Voronoi tiles. Our framework is able to handle tens of thousands of contours and points and can generate DEMs comprising more than 100 million samples. We provide quantitative comparison to commercial software and show the benefits of our approach. We furthermore show the robustness of our method on a massive set of old maps predating satellite acquisition. Compared to other methods, our framework is able to accurately and efficiently generate a final DEM despite inconsistencies, sparse or missing contours even for highly complex and cluttered maps. Therefore, this method has broad applicability for digitization and reconstruction of the world's old topographic maps that are often the only record of past landscapess and cultural heritage before their destruction under modern development.en
dc.language.isoenen
dc.subjectData acquisition and managementen
dc.subjectGeometry-based techniquesen
dc.subjectGeographical and geospatial visualizationen
dc.titleA Visual Framework for Digital Reconstruction of Topographic Mapsen
dc.typeTechnical Reporten
dc.contributor.departmentVisual Computing Center (VCC)en
dc.eprint.versionPre-printen
dc.contributor.institutionChair of Scientific Computing in Computer Science, Technische Universität Münchenen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
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