Abstract:
This paper presets a methodology and results of evaluating damaged building detection algorithms
using an object recognition task based on Differential Morphological Profile (DMP) for Very High Resolution
(VHR) remotely sensed images. The proposed approach involves several advanced morphological operators
among which an adaptive hit-or-miss transform with varying size, shape and gray level of the structuring
elements. IKONOS Satellite panchromatic images consisting of pre and post earthquake site of Sichuan area in
China were used. Morphological operation of opening and closing with constructions are applied for segmented
images. Unsupervised classification ISODATA algorithm is used for the feature extraction and the results
comparison with ground truth data, complex urban area before the earthquake gives 76% and same area wracked
after the earthquake gives 88% buildings detection on object based accuracy. This work is being extended to
extract shadows and non building objects for better classifications of building roof footprints.
