• DocumentCode
    2867689
  • Title

    Aircraft recognition from satellite images

  • Author

    Oturak, Mehmet ; Yuksel, Seniha Esen

  • Author_Institution
    Uzay Teknolojileri Arastirma Enstitusu, TUBITAK UZAY, Ankara, Turkey
  • fYear
    2015
  • fDate
    16-19 May 2015
  • Firstpage
    719
  • Lastpage
    722
  • Abstract
    In this work, rapid and high-accurate aircraft detection method in satellite images is developed. To this end, AdaBoost learning algorithm is used and Viola-Jones´ near real time and high-accurate face detector utilizing haar-like features is taken as reference. In existing studies, for a sub window to be positive, it must pass through all the strong classifiers as positive. However, in this work the strong classifier output values are summed up and compared to a threshold value as well. Therefore, besides the cascade structure´s ability to eliminate negative sub windows rapidly, more elaborate evaluation is made on the class of sub window, giving rise to a high performance classifier.
  • Keywords
    face recognition; image classification; image recognition; learning (artificial intelligence); object detection; remote sensing; AdaBoost learning algorithm; Viola-Jones near real time; aircraft detection method; aircraft recognition; cascade structure ability; classifier output values; haar-like features; high-accurate face detector; high-performance classifier; negative subwindow elimination; satellite images; threshold value; Aircraft; Boosting; Feature extraction; Image recognition; Real-time systems; Satellites; Support vector machines; AdaBoost; Aircraft Recognition; Classifier; Haar-like features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2015 23th
  • Conference_Location
    Malatya
  • Type

    conf

  • DOI
    10.1109/SIU.2015.7129927
  • Filename
    7129927