Embedded Image Processing Systems for Automatic Recognition of Cracks using UAVs

Aiming at the use of Unmanned Aerial Vehicle (UAV) in civil construction for autonomous inspection of building pathologies, this paper discusses some implementation alternatives of image processing algorithms for the detection of cracks in building facades. These algorithms should run in an embedded computing platform installed on UAVs. Two image processing algorithms for crack detection and classification were selected and different embedded system implementations were evaluated. A version of the algorithms running in a Matlab environment on a desktop computer, which can be used in an approach on which the image processing is done in the ground and the UAV is only applied for image acquisition, was used as a baseline for the comparison. This baseline is compared with implementations running on an embedded processor (a Raspberry PI, running a distribution of Debian ARM operating system) and with implementations on a Xilinx FPGA-board installed in the UAV. Different scenarios for the execution of a inspection task of building facades were defined and the obtained results are presented in the paper.