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
Link To Document