Crack detection is important in safety assessment of buildings. However, for the present there is still no crack detection
equipment available which can encompass both short-distance and long-distance examination functions. In view of
existing problems, this paper develops a portable digital building surface crack detector integrating short-distance and
long-distance examination functions. The crack detector can acquire images of building surface cracks and transmit the
images through USB interface to computer for postprocessing. It has the functions of image acquisition, image storage,
image processing and results display. Some experiments are performed at different distances and the measured results
are calibrated with standard elements. The experiments show that the minimum resolution of the detector is better than
0.01mm, and the measurement accuracy is better than 0.02mm when surveying cracks at a distance shorter than 2m.
When surveying cracks at a distance of 2 ~ 100m, both the minimum resolution and the measurement accuracy of the
detector are better than 0.5mm.
Because of the presence of cloud, the quality and application of data obtained in visible light and infrared bands are
affected when remote sensing images are generated. This paper proposes an automatic selection method with the best
cut-off frequency to remove the effect of thin cloud in remote sensing images quickly and efficiently. Based on the
homomorphic filtering method of the simple thin cloud imaging model and the self-similarity of the spatial form of thin
cloud and haze, this paper uses the multi-fractal technology and the filtering technology of the S-A model (power
spectrum-area model) to determine the filtering radius automatically. The experiments of removing thin cloud and haze
for remote sensing images show that the filtering technology of the S-A model is related to the spatial form of image
contents directly. Compared with usual filtering technologies which choose frequency as radius, this method can not
only achieve rapid and automatic filtering of remote sensing images, but also remove the effect of thin cloud in remote
sensing images effectively.