• DocumentCode
    1961258
  • Title

    Aircraft Target Recognition: A novel approach for features extraction from ISAR images

  • Author

    Saidi, M.N. ; Toumi, A. ; Hoeltzener, B. ; Khenchaf, A. ; Aboutajdine, D.

  • Author_Institution
    Lab. E3I2-EA3876, ENSIETA, Brest, France
  • fYear
    2009
  • fDate
    12-16 Oct. 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In this paper, we present a system for Automatic Target Recognition (ATR) based on ISAR images. The methodology used is based on knowledge discovery from data (KDD process) process adapted to radar field. The shape extraction is the most important step in recognition system. However, we propose a new approach for Target shape extraction based on combination of Smallest Univalue Segment Assimilating Nucleus (SUSAN) method and Variational Level Set (VLS). The feature vector is then represented by Fourier descriptors of each target shape. Finally, recognition scheme is achieved by both: Support Vectors Machine (SVM) and K Nearest Neighbors (KNN) classifiers.
  • Keywords
    airborne radar; aircraft; feature extraction; radar computing; radar imaging; radar target recognition; support vector machines; synthetic aperture radar; Fourier descriptors; ISAR images; aircraft target recognition; automatic target recognition; features extraction; inverse synthetic aperture radar images; nearest neighbors classifiers; radar field; smallest univalue segment assimilating nucleus; support vectors machine; target shape extraction; variational level set; Aircraft; Data mining; Feature extraction; Image segmentation; Level set; Radar imaging; Shape; Support vector machine classification; Support vector machines; Target recognition; ATR; Classification; ISAR; KDD; Level set; SUSAN; shape extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radar Conference - Surveillance for a Safer World, 2009. RADAR. International
  • Conference_Location
    Bordeaux
  • Print_ISBN
    978-2-912328-55-7
  • Type

    conf

  • Filename
    5438432