A simple and efficient approach for coarse segmentation of Moroccan coastal upwelling

A. Tamim, K. Minaoui, K. Daoudi, Hussein M. Yahia, A. Atillah, M. F. Smiej, D. Aboutajdine
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引用次数: 20

Abstract

In this work, we aim to develop a simple and fast algorithm using conventional methods in images segmentation for the automatic detection and extraction of upwelling areas, in the coastal region of Morocco, from the sea surface temperature (SST) satellite images. Our approach is based on the evaluation and comparison between two unsupervised classification methods, Otsu and Fuzzy C-means, and explores the applicability of these methods to our classification problem. The latter consists in coarse detection of the main thermal front that separates coastal cold upwelling waters from the remaining ocean waters. The algorithm has been applied and validated by an oceanographer over a database of 66 SST images corresponding to southern Moroccan coastal upwelling of the years 2004, 2005, 2007 and 2009. The results indicate that the proposed algorithm revealed is promising and reliable on different upwelling scenarios and for a wide variety of oceanographic conditions.
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摩洛哥海岸上升流粗分割的一种简单有效的方法
在这项工作中,我们的目标是利用传统的图像分割方法开发一种简单快速的算法,用于从海面温度(SST)卫星图像中自动检测和提取摩洛哥沿海地区的上升流区域。我们的方法是基于对两种无监督分类方法Otsu和模糊C-means的评价和比较,并探讨这些方法对我们的分类问题的适用性。后者包括对分离沿海冷上升流与其余海水的主热锋的粗略探测。该算法已由一位海洋学家在一个数据库上进行了应用和验证,该数据库包含2004、2005、2007和2009年摩洛哥南部沿海上升流的66幅海温图像。结果表明,所提出的算法在不同的上升流情景和各种海洋条件下是有希望和可靠的。
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