Automatic Water Eddy Detection in SST Maps Using Random Ellipse Fitting and Vectorial Fields for Image Segmentation

Susana Maria dos Santos Nascimento M. de Almeida

doi:10.1007/11893318_11

Automatic Water Eddy Detection in SST Maps Using Random Ellipse Fitting and Vectorial Fields for Image Segmentation

Susana Maria dos Santos Nascimento M. de Almeida

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

20 Citations (Scopus)

Abstract

The impact of water eddies off the Iberian coast in the chemistry and biology of the ocean ecosystems, on the circulation of ocean waters and on climate still needs to be studied. The task of identifying water eddies in sea surface temperature maps (SST) is time-consuming for oceanographers due to the large number of SST available. This motivates the present investigation aiming to develop an automatic system capable of performing that task. The system developed consists of a pre-processing stage where a vectorial field is calculated using an optical flow algorithm with one SST map and a matrix of zeros for input. Next, a binary image of the modulus of the vectorial field is created using an iterative thresholding algorithm. Finally, five edge points of the binary image, classified according to their gradient vector direction, are randomly selected and an ellipse corresponding to a water eddy fitted to them.

Original language	Unknown
Title of host publication	Lecture Notes in Artificial Intelligence
Pages	77-88
DOIs	https://doi.org/10.1007/11893318_11
Publication status	Published - 1 Jan 2006
Event	International Conference on Discovery Science (DS-2006) - Duration: 1 Jan 2006 → …

Conference

Conference	International Conference on Discovery Science (DS-2006)
Period	1/01/06 → …

Access to Document

10.1007/11893318_11

Cite this

@inproceedings{574a77c0a71a452ca695fa28967a1d4f,

title = "Automatic Water Eddy Detection in SST Maps Using Random Ellipse Fitting and Vectorial Fields for Image Segmentation",

abstract = "The impact of water eddies off the Iberian coast in the chemistry and biology of the ocean ecosystems, on the circulation of ocean waters and on climate still needs to be studied. The task of identifying water eddies in sea surface temperature maps (SST) is time-consuming for oceanographers due to the large number of SST available. This motivates the present investigation aiming to develop an automatic system capable of performing that task. The system developed consists of a pre-processing stage where a vectorial field is calculated using an optical flow algorithm with one SST map and a matrix of zeros for input. Next, a binary image of the modulus of the vectorial field is created using an iterative thresholding algorithm. Finally, five edge points of the binary image, classified according to their gradient vector direction, are randomly selected and an ellipse corresponding to a water eddy fitted to them.",

keywords = "random ellipse detection, image segmentation, optical flow, water eddy",

author = "Almeida, {Susana Maria dos Santos Nascimento M. de}",

year = "2006",

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doi = "10.1007/11893318_11",

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T1 - Automatic Water Eddy Detection in SST Maps Using Random Ellipse Fitting and Vectorial Fields for Image Segmentation

AU - Almeida, Susana Maria dos Santos Nascimento M. de

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N2 - The impact of water eddies off the Iberian coast in the chemistry and biology of the ocean ecosystems, on the circulation of ocean waters and on climate still needs to be studied. The task of identifying water eddies in sea surface temperature maps (SST) is time-consuming for oceanographers due to the large number of SST available. This motivates the present investigation aiming to develop an automatic system capable of performing that task. The system developed consists of a pre-processing stage where a vectorial field is calculated using an optical flow algorithm with one SST map and a matrix of zeros for input. Next, a binary image of the modulus of the vectorial field is created using an iterative thresholding algorithm. Finally, five edge points of the binary image, classified according to their gradient vector direction, are randomly selected and an ellipse corresponding to a water eddy fitted to them.

AB - The impact of water eddies off the Iberian coast in the chemistry and biology of the ocean ecosystems, on the circulation of ocean waters and on climate still needs to be studied. The task of identifying water eddies in sea surface temperature maps (SST) is time-consuming for oceanographers due to the large number of SST available. This motivates the present investigation aiming to develop an automatic system capable of performing that task. The system developed consists of a pre-processing stage where a vectorial field is calculated using an optical flow algorithm with one SST map and a matrix of zeros for input. Next, a binary image of the modulus of the vectorial field is created using an iterative thresholding algorithm. Finally, five edge points of the binary image, classified according to their gradient vector direction, are randomly selected and an ellipse corresponding to a water eddy fitted to them.

KW - random ellipse detection

KW - image segmentation

KW - optical flow

KW - water eddy

U2 - 10.1007/11893318_11

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M3 - Conference contribution

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BT - Lecture Notes in Artificial Intelligence

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