FUZZY C MEAN CLUSTERING ALGORITHM FOR OIL SPILL MONITORING AND DETECTION

Authors

  • Mukta Jagdish Research Scholar, Department of Computer Science and Engineering, School of Engineering, Vels Institute of Science Technology &Advanced Studies (VISTAS), Vels University, Chennai, TN, India.
  • Jerritta.S Research Supervisor, Associate Professor (Electronics and Communication Engineering), School of Engineering, Vels Institute of Science Technology &Advanced Studies (VISTAS), Vels University, Chennai, TN, India

Keywords:

Oil spill, Gulf of Mexico, pattern, tracking, ASAR RADARSAT-2, Morphological Techniques

Abstract

This research aims to detect and monitor oil spills using fuzzy c mean clustering algorithm using advance
synthetic aperture radar images in Gulf of Mexico. Oil spill harmed wildlife habitats and maritime spices life. To overcome
this problem radar image was used for regular monitoring which improves over all oil spill problems by various approaches.
In fuzzy c mean clustering algorithm it allow one object belongs to two or more object in clusters form. Similarly object or
data will be placed in one place. This method improves frequently using pattern recognition, iterative optimization objective
function and fuzzy partitioning. Main objective is to regular monitor spills in ocean with faster information gathering and oil
spill detection programs. This research was conducted to find out oil spill pattern, patches and tracking spills in particular
areas.

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Published

2018-02-25

How to Cite

Mukta Jagdish, & Jerritta.S. (2018). FUZZY C MEAN CLUSTERING ALGORITHM FOR OIL SPILL MONITORING AND DETECTION. International Journal of Advance Engineering and Research Development (IJAERD), 5(2), 732–736. Retrieved from https://ijaerd.org/index.php/IJAERD/article/view/2474

Issue

Vol. 5 No. 2 (2018): Volume 5 Issue 2 February 2018

Section

Articles

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