ADAPTIVE THRESHOLDING AND MORPHOLOGICAL ALGORITHM FOR MONITORING AND TRACKING OIL SPILLS
Keywords:
Oil spill, pattern, tracking, Morphological Techniques, adaptive thresholdingAbstract
This work aimed to compare adaptive thresholding and morphological techniques for oil spill detection and
identification 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. As
we know histogram based analysis requires one pass through pixel in satellite image. Morphological operation is based on
the structure analysis, in which some components are selected among all, which satisfy Gestalt principles such as (1)
Proximity state that two objects are easier regard as a single object by a human being if those objects are close to each
other. (2) Good continuation states that objects are easier regard as a single object if they can be continued from one to
other. After analysing both algorithm it results that morphological algorithm is more suitable for detection of oil spill with
less time duration using radar images than adaptive thresholding technique.
