• DocumentCode
    714671
  • Title

    A Novel approach for automatic ship type classification

  • Author

    Kacar, Umit ; Kumlu, Deniz ; Kirci, Murvet

  • Author_Institution
    Elektron. ve Haberlesme Muhendisligi Bolum, Istanbul Tek. Univ., İstanbul, Turkey
  • fYear
    2015
  • fDate
    16-19 May 2015
  • Firstpage
    2153
  • Lastpage
    2156
  • Abstract
    This work classifies the ship types from color images by using cameras mounted on ships. Our data set contains 10 different ship types. The synthetic images used for training imported from Google 3D Warehouse. Test data set imported from Google Images and contains real ship images. This work aims to classify real ship images by using synthetic images. We present a novel approach for combining four features extracted from synthetic images and we have achieved % 90 accuracy.
  • Keywords
    cameras; feature extraction; image classification; image colour analysis; marine engineering; object recognition; ships; Google 3D Warehouse; Google Images; automatic ship type classification; cameras; color images; feature extraction; real ship images; synthetic images; Color; Feature extraction; Google; Image recognition; Marine vehicles; Solid modeling; Ship type classification; feature combining; feature extraction; object recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2015 23th
  • Conference_Location
    Malatya
  • Type

    conf

  • DOI
    10.1109/SIU.2015.7130299
  • Filename
    7130299