Texture-Based Airport Runway Detection

Aytekin O., Zongur U., HALICI U.

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, cilt.10, sa.3, ss.471-475, 2013 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 10 Sayı: 3
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1109/lgrs.2012.2210189
  • Dergi Adı: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.471-475
  • Anahtar Kelimeler: Adaboost algorithm, airport runway detection, satellite images, textural features, FEATURES, RECOGNITION, EXTRACTION
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

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.