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R. Duda, P. Hart (1972)
Use of the Hough transformation to detect lines and curves in picturesCommun. ACM, 15
R. Lemos, M. Loja, J. Rodrigues, J. Rodrigues (2016)
Photogrammetric analysis of rubble mound breakwaters scale model tests, 3
This contribution was selected by the Scientific Committee for publication as an extended paper
AbstractA rubble mound breakwater (BW) is a coastal engineering structure built for purposes of harbor protection in areas with severe wave regimes. Block displacements can lead to a structure weakening, making the harbor more vulnerable to waving hazard. During the phase of BW design/rehabilitation the effectiveness evaluation of both the shape and the protective elements is made throughout 3D scale models, built inside wave basins or wave flumes. The experiment consists of simulating the impact of the swell on the model. During the process, 3D point cloud (PC) data is recorded with depth sensors, or later generated by photogrammetry from image data. Surface changes are obtained by comparing PCs, with the estimation of depth differences. However, inaccurate face delimitation on PCs may lead to less conclusive results of blocks’ location and motion. In this study, it is proposed an edge-based image segmentation method, based on the Hough transformation algorithm, in order to obtain the straight edges of the block’s faces in images of breakwater models. By crossing each resulting polygonal region with the PC depth data of the block, a regular plane surface can be adjusted to the 3D points, from which the block’s center point can be geometrically estimated. For this study RGB and PC data regions were selected from a scanned BW model, built with small cubic concrete blocks. The results obtained reinforce the positive contribution that the proposed image segmentation methodology can provide, regarding the improvement of displacement accuracy and spending time analysis, in BW monitoring work.
Journal of Applied Geodesy – de Gruyter
Published: Apr 1, 2023
Keywords: breakwaters; Hough transformation; image segmentation; point clouds
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