Paper
5 May 2006 Parallel algorithm for linear feature detection from airborne LiDAR data
Author Affiliations +
Abstract
Linear features from airport images correspond to runways, taxiways and roads. Detecting runways helps pilots to focus on runway incursions in poor visibility conditions. In this work, we attempt to detect linear features from LiDAR swath in near real time using parallel implementation on G5-based apple cluster called Xseed. Data from LiDAR swath is converted into a uniform grid with nearest neighbor interpolation. The edges and gradient directions are computed using standard edge detection algorithms such as Canny's detector. Edge linking and detecting straight-line features are described. Preliminary results on Reno, Nevada airport data are included.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Manohar Mareboyana and Paul Chi "Parallel algorithm for linear feature detection from airborne LiDAR data", Proc. SPIE 6209, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications III, 62090I (5 May 2006); https://doi.org/10.1117/12.668782
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
LIDAR

Detection and tracking algorithms

Image processing

Image segmentation

Data conversion

Edge detection

Image processing algorithms and systems

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