COMPARING K- MEAN CLUSTER AND ACTIVE CONTOUR FOR OIL SPILL DETECTION
| Author(s) | : | Mukta Jagdish, Jerritta.S |
| Institution | : | Research Scholar, Department of Computer Science and Engineering, School of Engineering, Vels Institute of Science Technology &Advanced Studies (VISTAS), Vels University, Chennai, TN, India. |
| Published In | : | Vol. 5, Issue 2 — February 2018 |
| Page No. | : | 1066-1071 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
This work aimed to compare k- mean clustering and active contour techniques for oil spill detection andidentification using ASAR images in Gulf of Mexico. This comparing of algorithms helps us to find out tracking of oil spill,oil spill area, dark patches and spill patterns in radar images which help in regular monitoring of oil spill coverage area. Aswe know K mean clustering is a vector quantization method used for oil spill detection. Here each element is partition into kclusters which belongs to nearest mean, act as prototypes for the cluster. It works on dividing data cell into voronoi cells. Kmean cluster determine comparable spatial extent clusters. It classifies data which is new into existing clusters which calledas centroid nearest classifier. After analysing both algorithms it results that k mean clustering is more suitable for detectionof oil spill with less time duration using radar images than active contour
Mukta Jagdish, Jerritta.S, “COMPARING K- MEAN CLUSTER AND ACTIVE CONTOUR FOR OIL SPILL DETECTION”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 2, pp. 1066-1071, February 2018.
