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GVU Technical Report
Number: GIT-GVU-02-15
Title: Semi-Automated Landscape Feature
Extraction and Modeling
Authors:
Tony Wasilewski,
Nickolas Faust,
Matthew Grimes,
William Ribarsky
Abstract:
We have developed a semi-automated procedure for generating correctly located 3D tree objects from overhead
imagery. Cross-platform software partitions arbitrarily large, geocorrected and geolocated imagery into
manageable sub-images. The user manually selects tree areas from one or more of these sub-images. Samples
are taken from these areas, and color statistics are computed. Tree areas are detected in subsequent images.
Tree group blobs are then narrowed to lines using a special thinning algorithm which retains the topology of
the blobs, and also stores the thickness of the parent blob. Maxima along these thinned tree groups are found,
and used as individual tree locations within the tree group. Magnitudes of the local maxima are used to scale
the radii of the tree objects. Grossly overlapping trees are culled based on a comparison of tree-tree distance
to combined radii. Tree color is randomly selected based on the distribution of sample tree pixels, and height
is estimated from tree radius. The final tree objects (perpendicular intersecting tree cutouts) are then inserted
into a terrain database which can be navigated by VGIS 1 , a high-resolution global terrain visualization system
developed at Georgia Tech.
Keywords: Feature extraction, terrain visualization
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