A Novel Approach for Automatic Ship Type Classification


Kacar U., Kumlu D., Kırcı M.

23nd Signal Processing and Communications Applications Conference (SIU), Malatya, Turkey, 16 - 19 May 2015, pp.2153-2156 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Malatya
  • Country: Turkey
  • Page Numbers: pp.2153-2156

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.