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Efficient Airport Detection Using Line Segment Detector and Fisher Vector Representation
Date
2016-08-01
Author
Budak, Umit
Halıcı, Uğur
Sengur, Abdulkadir
Karabatak, Murat
Xiao, Yang
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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In this letter, a two-stage method for airport detection on remote sensing images is proposed. In the first stage, a new algorithm composed of several line-based processing steps is used for extraction of candidate airport regions. In the second stage, the scale-invariant feature transformation and Fisher vector coding are used for efficient representation of the airport and nonairport regions and support vector machines employed for classification. In order to evaluate the performance of the proposed method, extensive experiments are conducted on airports around the world with different layouts. The measures used in the evaluation are accuracy, sensitivity, and specificity. The proposed method achieved an accuracy of 94.6%, which was benchmarked with two previous methods to prove its superiority.
Subject Keywords
Airport detection
,
Fisher vector (FV)
,
Line segment detector (LSD)
,
Remote sensing images (RSIs)
,
Sscale-invariant feature transform (SIFT) features
,
Support vector machines (SVMs)
URI
https://hdl.handle.net/11511/39356
Journal
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
DOI
https://doi.org/10.1109/lgrs.2016.2565706
Collections
Department of Electrical and Electronics Engineering, Article