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Crack detection for bridge bottom surfaces via remote sensing techniques is undergoing a revolution in the last few years. For such\udapplications, a large amount of images, acquired with high-resolution industrial cameras close to the bottom surfaces with some mobile\udplatform, are required to be stitched into a wide-view single composite image. The conventional idea of stitching a panorama with\udthe affine model or the homographic model always suffers a series of serious problems due to poor texture and out-of-focus blurring\udintroduced by depth of field. In this paper, we present a novel method to seamlessly stitch these images aided by 3D structure lines of\udbridge bottom surfaces, which are extracted from 3D camera data. First, we propose to initially align each image in geometry based\udon its rough position and orientation acquired with both a laser range finder (LRF) and a high-precision incremental encoder, and these\udimages are divided into several groups with the rough position and orientation data. Secondly, the 3D structure lines of bridge bottom\udsurfaces are extracted from the 3D cloud points acquired with 3D cameras, which impose additional strong constraints on geometrical\udalignment of structure lines in adjacent images to perform a position and orientation optimization in each group to increase the local\udconsistency. Thirdly, a homographic refinement between groups is applied to increase the global consistency. Finally, we apply a\udmulti-band blending algorithm to generate a large-view single composite image as seamlessly as possible, which greatly eliminates\udboth the luminance differences and the color deviations between images and further conceals image parallax. Experimental results on\uda set of representative images acquired from real bridge bottom surfaces illustrate the superiority of our proposed approaches

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

OPTIMAL IMAGE STITCHING FOR CONCRETE BRIDGE BOTTOM SURFACES AIDED BY 3D STRUCTURE LINES