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Detection of Moroccan coastal upwelling in SST images using the Expectation-Maximization
- Source :
- ISVC'14: 10th International Symposium on Visual Computing
- Publication Year :
- 2015
- Publisher :
- IEEE, 2015.
-
Abstract
- International audience; This paper proposes an unsupervised algorithm for automatic detection and segmentation of upwelling region in Moroccan Atlantic coast using the Sea Surface Temperature (SST) satellite images. This has been done by exploring the Expectation-Maximization algorithm. The good number of clus- ters that best reproduces the shape of upwelling areas is selected by using the two popular Davies-Bouldin and Dunn indices. Area opening technique is developed that is used to remove and discarded the residuals noise in offshore waters not belonging to the upwelling region. The complete system has been validated by an oceanographer using a database of 30 SST images of the year 2007, demonstrating its capability and robustness for precise detection of Moroccan coastal upwelling.
- Subjects :
- [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere
Upwelling
Meteorology
Dunn index
Davies-Bouldin index
Area opening
Image segmentation
Expectation-Maximisation
Sea surface temperature
Geography
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Robustness (computer science)
Expectation–maximization algorithm
Sea Surface Temperature
Segmentation
Satellite
Submarine pipeline
[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2015 Intelligent Systems and Computer Vision (ISCV)
- Accession number :
- edsair.doi.dedup.....7518aa47cf63d2897dcc097a3736eb83
- Full Text :
- https://doi.org/10.1109/isacv.2015.7106195