Record Details

Classification of oil spill in the Krishna-Godavari offshore using ERS-1 SAR images with a fuzzy logic approach

NOPR - NISCAIR Online Periodicals Repository

View Archive Info
 
 
Field Value
 
Title Classification of oil spill in the Krishna-Godavari offshore using ERS-1 SAR images with a fuzzy logic approach
 
Creator Ramakrishnan, R.
Majumdar, T. J.
 
Subject Synthetic Aperture Radar
Oil Spill Detection
Feature Extraction
Fuzzy Logic
Krishna-Godavari Offshore etc.
 
Description 431-436
In the present
study new features are extracted from the dark spot and fuzzy based techniques
were utilized for classifications of the dark spot into oil spill and look
alike. Threshold is defined for detection of dark spot, which is obtained from
histogram analysis, where the image histograms consist of two peaks. For scenes
devoid of two peaks in the histogram, an empirical formula is developed from
the scene statistics, which designate the threshold for segmentation of the
dark spot. A centerline concept is introduced which bisects the slick along the
major axis. This is further used to determine the width, shape and orientation
of the suspected slick. Abrupt turn and curving of the slick is also monitored
from the centerline. According to the characteristic of each feature, separate
membership functions were assigned to obtain its fuzzy set. Few features were
identified to have high discriminatory power, whose values were having marked
contrast for oil spill and look alike. Five classes were defined: 1) oil spill,
2) tending to oil spill, 3) uncertain, 4) tending to look alike and 5) look
alike. From 30 dark spots obtained from six ERS-1 SAR scenes, six were
classified as oil spill and four dark spots as look alike. Six dark spots were
classified as tending to oil spill and five as tending to look alike, whereas
classification of nine dark spots was found to be uncertain.
 
Date 2013-09-02T12:12:29Z
2013-09-02T12:12:29Z
2013-08
 
Type Article
 
Identifier 0975-1033 (Online); 0379-5136 (Print)
http://hdl.handle.net/123456789/20899
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source IJMS Vol.42(4) [August 2013]