By Topic

Texture-Based Airport Runway Detection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Aytekin, O. ; Dept. of Electr. & Electron. Eng., Middle East Tech. Univ., Ankara, Turkey ; Zongur, U. ; Halici, U.

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.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:10 ,  Issue: 3 )