Ship detection on optical remote sensing images is getting great attention; however, some images called wakesship have not been taken into account yet. Current works in ship detection are focusing on in-shore detection where ships are in calm; furthermore, their methods get high Intersection Over Union (IoU), above 70%, but when computing IoU using only wakes-ship images the ratio is 22%. In this paper, it is presented a new framework to improve ship segmentation on wakes-ship images. In order to achieve this goal, it was considered HSV color space and histograms. First, ship detection was done using state-of-the-art ship detection methods. Second, bin histograms in HSV color space was used to get the colors that rely on wakes. Finally, the removal of wakes from ships was done using some discriminative properties. In this way, the increase of the IoU performance at wake-ship segmentation goes from 22% to 63%, which is an improvement of 186%.
|Number of pages||5|
|Journal||International Journal of Advanced Computer Science and Applications|
|State||Published - 2018|
Bibliographical notePublisher Copyright:
© 2018, (IJACSA) International Journal of Advanced Computer Science and Applications.
- HSV color space
- Intersection over union
- Optical remote sensing
- Ship detection
- Wakes-ship removal