DocumentCode :
2554368
Title :
Detection of oil spills using feature extraction and threshold based segmentation techniques
Author :
Vyas, Garima ; Bhan, Anupama ; Gupta, Divya
Author_Institution :
Amity Sch. Of Eng. & Technol., Amity Univ., Noida, India
fYear :
2015
fDate :
19-20 Feb. 2015
Firstpage :
579
Lastpage :
583
Abstract :
Satellite images can improve the possibilities for the detection of oil spills as they cover large areas and offer an economical and easier way of continuous coast areas patrolling. There are many common techniques to detect dark formations on the SAR images. This paper mainly focuses on method with spot feature extraction and global thresholding. The main approach used in this paper is detecting the dark spots, using local and global threshold algorithms. For each dark spot, a number of features are calculated in order to classify the slick as either oil or other possible geographical or natural components of water. The proposed threshold algorithm, initially analyzes the SAR images, and then assigns a probability to the dark spot to indicate whether it is an oil spill or look alike.
Keywords :
feature extraction; geophysical image processing; geophysical techniques; image segmentation; marine pollution; oil pollution; synthetic aperture radar; coast areas patrolling; dark spot detection; global threshold algorithm; local threshold algorithm; oil spill detection; satellite images; spot feature extraction; threshold based segmentation technique; water geographical component; water natural component; Feature extraction; Image segmentation; MODIS; Remote sensing; Satellites; Standards; Synthetic aperture radar; Gamma Correction; Global Thresholding; Local Thresholding; Masking; Oil Spills;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Integrated Networks (SPIN), 2015 2nd International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-5990-7
Type :
conf
DOI :
10.1109/SPIN.2015.7095433
Filename :
7095433
Link To Document :
بازگشت