| Summary: | PhD, Faculty of Engineering and the Built Environment, University of the Witwatersrand, 2010 === Informal settlements are a growing world-wide phenomenon. Up-to-date spatial
information mapping settlements is essential for a variety of end-user applications
from planning settlement upgrading to monitoring expansion and infill. One method
of gathering this information is through the analysis of nadir-view aerial imagery and
the automated or semi-automated extraction of individual shacks. The problem of
shack detection and delineation in, particularly South African, informal settlements
is a unique and difficult one. This is primarily due to the inhomogeneous appearance
of shack roofs, which are constructed from a variety of disparate materials, and
the density of shacks. Previous research has focused mostly on the use of height
data in conjunction with optical images to perform automated or semi-automated
shack extraction. In this thesis, a novel approach to automating shack extraction is
presented and prototyped, in which the appearance of shack roofs is homogenised,
facilitating their detection. The main features of this strategy are: construction of
an anisotropic scale-space from a single source image and detection of hypotheses
at multiple scales; simplification of hypotheses' boundaries through discrete curve
evolution and regularisation of boundaries in accordance with an assumed shack
model - a 4-6 sided, compact, rectilinear shape; selection of hypotheses competing
across scales using fuzzy rules; grouping of hypotheses based on their support
for one another, and localisation and re-regularisation of boundaries through the
incorporation of image edges. The prototype's performance is evaluated in terms of
standard metrics and is analysed for four different images, having three different sets
of imaging conditions, and containing well over a hundred shacks. Detection rates in
terms of building counts vary from 83% to 100% and, in terms of roof area coverage,
from 55% to 84%. These results, each derived from a single source image, compare
favourably with those of existing shack detection systems, especially automated ones
which make use of richer source data. Integrating this scale-space approach with
height data offers the promise of even better results.
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