Detection of sea targets from thermal images


Yaslan Y., Gunsel B.

IEEE 12th Signal Processing and Communications Applications Conference, Kusadasi, Türkiye, 28 - 30 Nisan 2004, ss.672-675 identifier identifier

  • Doi Numarası: 10.1109/siu.2004.1338620
  • Basıldığı Şehir: Kusadasi
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.672-675

Özet

In this paper, sea targets detection problem from thermal (IR) images is solved by using statistical classification methods. Background modelling is achieved via principle component analysis (PCA) followed by a two-class Bayes classification step, i.e., target or sea. A wavelet-denoising block is added to the system resulting in a significant increase in the detection performance. K-means clustering is also implemented to explore the target detection accuracy without training. It is concluded that the PCA training provides high detection accuracy while the K-means clustering mostly fails to classify the sea targets.