Texture-Based Airport Runway Detection

Date

2013-05-01

Author

Aytekin, O.
Zongur, U.
Halıcı, Uğur

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The automatic detection of airports is essential due to the strategic importance of these targets. In this letter, a runway detection method based on textural properties is proposed since they are the most descriptive element of an airport. Since the best discriminative features for airport runways cannot be trivially predicted, the Adaboost algorithm is employed as a feature selector over a large set of features. Moreover, the selected features with corresponding weights can provide information on the hidden characteristics of runways. Thus, the Adaboost-based selected feature subset can be used for both detecting runways and identifying their textural characteristics. Thus, a coarse representation of possible runway locations is obtained. The performance of the proposed approach was validated by experiments carried on a data set of large images consisting of heavily negative samples.

Subject Keywords

Adaboost algorithm, Textural features, Satellite images, Airport runway detection

URI

https://hdl.handle.net/11511/43189

Journal

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS

DOI

https://doi.org/10.1109/lgrs.2012.2210189

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

O. Aytekin, U. Zongur, and U. Halıcı, “Texture-Based Airport Runway Detection,” IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, pp. 471–475, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/43189.