Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17664
Title: Semiautomatic airport runway extraction using a line-finder-aided level set evolution
Authors: Li, Z 
Liu, Z 
Shi, W 
Keywords: Google earth images
Line detection
Long straight line finder
Region-based level set method
Semiautomatic airport runway extraction
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE Journal of selected topics in applied earth observations and remote sensing, 2014, v. 7, no. 12, 6719507, p. 4738-4749 How to cite?
Journal: IEEE journal of selected topics in applied earth observations and remote sensing 
Abstract: In recent years, airport runway extraction has become increasingly important for various engineering applications. Existing approaches for airport runway extraction primarily focus on locating the airport roughly, i.e., determining whether an airport is present or not, but not delineating the airport runway accurately. This study develops a novel method for semiautomatic airport runway extraction from Google earth images by integrating a long straight line finder and a region-based level set evolution (LSE). Specifically, we start by detecting the long straight lines that most likely represent airport runway boundaries in the original images. Then, based on the extracted lines, we propose a method for semiautomatic generation of initial level curves for the LSE. Furthermore, for accurate extraction of the entire airport runways, a fast region-based LSE is used to evolve the initial level curves toward the desired boundaries. Experiments validate that the proposed method is capable of semiautomatically extracting objects with complex geometrical shapes and topological structures from challenging backgrounds. Compared with other state-of-the-art approaches, the proposed method has much fewer parameters and is more computationally efficient while achieving object extraction accuracy comparable to other approaches.
URI: http://hdl.handle.net/10397/17664
ISSN: 1939-1404
EISSN: 2151-1535
DOI: 10.1109/JSTARS.2014.2298332
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