Oil Spill Detection using Segmentation based Approaches

B. Alacid

Abstract

This paper presents a description and comparison of two segmentation methods for the oil spill detection in the sea surface. SLAR sensors acquire video sequences from which snapshots are extracted for the detection of oil spills. Both approaches are segmentation based on graph techniques and J-image respectively. Finally, the aim of applying both approaches to SLAR snapshots, as shown, is to detect the largest part of the oil slick and minimize the false detection of the spill.

References

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Paper Citation


in Harvard Style

Alacid B. (2017). Oil Spill Detection using Segmentation based Approaches . In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-222-6, pages 442-447. DOI: 10.5220/0006191504420447


in Bibtex Style

@conference{icpram17,
author={B. Alacid},
title={Oil Spill Detection using Segmentation based Approaches},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2017},
pages={442-447},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006191504420447},
isbn={978-989-758-222-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Oil Spill Detection using Segmentation based Approaches
SN - 978-989-758-222-6
AU - Alacid B.
PY - 2017
SP - 442
EP - 447
DO - 10.5220/0006191504420447