Oil Spill Detection using Segmentation based Approaches
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http://hdl.handle.net/10045/75570
Title: | Oil Spill Detection using Segmentation based Approaches |
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Authors: | Mira Martínez, Damián | Gil, Pablo | Alacid Soto, Beatriz | Torres, Fernando |
Research Group/s: | Automática, Robótica y Visión Artificial |
Center, Department or Service: | Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal |
Keywords: | Oils Spill Detection | Remote Sensing | Segmentation | Slar Data |
Knowledge Area: | Ingeniería de Sistemas y Automática |
Issue Date: | 28-Feb-2017 |
Publisher: | SciTePress |
Citation: | Mira, D., et al. (2017). “Oil Spill Detection using Segmentation based Approaches”. In: Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2017), 442-447. doi:10.5220/0006191504420447 |
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. |
Sponsor: | This work was funded by Ministry of Economy and Competitiveness and supported by Spanish project (RTC-2014-1863-8). |
URI: | http://hdl.handle.net/10045/75570 |
ISBN: | 978-989-758-222-6 |
DOI: | 10.5220/0006191504420447 |
Language: | eng |
Type: | info:eu-repo/semantics/conferenceObject |
Rights: | © 2017 by SCITEPRESS – Science and Technology Publications, Lda. |
Peer Review: | si |
Publisher version: | https://doi.org/10.5220/0006191504420447 |
Appears in Collections: | INV - AUROVA - Comunicaciones a Congresos Internacionales INV - HURO - Comunicaciones a Congresos, Conferencias, etc. |
Files in This Item:
File | Description | Size | Format | |
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ICPRAM_2017_62_CR_final.pdf | Versión final (acceso restringido) | 426,72 kB | Adobe PDF | Open Request a copy |
ICPRAM_2017_62_CR.pdf | Versión revisada (acceso abierto) | 524,86 kB | Adobe PDF | Open Preview |
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