Automated search for livestock enclosures of rectangular shape in remotely sensed imagery

Abstract

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 proportions. 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. Its nodes represent linear segments and edges encode the above constraints. We tested our approach on a set of aerial and GeoEye-1 satellite images of 0.5m resolution that contain ruined livestock enclosures of approximately rectangular shape. The approach showed encouraging results in finding configurations of linear segments originating from the objects of our interest.