We introduce an approach for the detection of approximately rectangular
structures in gray scale images. Our research is motivated by the Silvretta
Historica project that aims at automated detection of remains of livestock
enclosures in remotely sensed images of alpine regions. The approach allows
detection of enclosures with linear sides of various sizes and aspect ratios.
It is robust to incomplete or fragmented rectangles and tolerates deviations
from a perfect rectangular shape. Morphological operators are used to extract
linear features. They are grouped into parameterized linear segments by means
of a local Hough transform. To identify appropriate configurations of linear
segments we define convexity and angle constraints. Configurations meeting
these constraints are rated by a proposed rectangularity measure that discards
overly fragmented configurations and configurations with more than one side
completely missing. The search for appropriate configurations is efficiently
performed on a graph with nodes corresponding to line segments and with edges
encoding spatial relationships between lines. We tested our approach on a set
of
aerial and GeoEye-1 satellite images of 0.5m resolution that contain ruined
livestock enclosures of rectangular shape. The approach showed encouraging
results in finding configurations of linear segments originating from the
objects of our interest.

More details can be found at
http://www.informatik.uni-konstanz.de/saupe/forschung/laufende-projekte/detection-of-archaeological-sites-in-high-resolution-remotely-sensed-imagery/