OIL SPILL IDENTIFICATION IN VISIBLE SENSOR IMAGING USING AUTOMATED CROSS CORRELATION WITH CRUDE OIL IMAGE FILTERS

Authors

  • G Ofualagba FEDERAL UNIVERSITY OF PETROLEUM RESOURCES (FUPRE), P.M.B. 1221, EFFURUN, DELTA STATE, NIGERIA
  • DU Onyishi FEDERAL UNIVERSITY OF PETROLEUM RESOURCES (FUPRE), P.M.B. 1221, EFFURUN, DELTA STATE, NIGERIA

Keywords:

Crude Oil Spill Detection, Crude oil image filters, Cross correlation, Visible sensor imaging, Oil Spill Segmentation.

Abstract

An algorithm for detection of crude oil spills in visible light images has been developed and tested on 50 documented crude oil spill images from Shell Petroleum Development Company (SPDC) Nigeria. A set of three 25 x 25 pixels crude oil filters, with unique red, green, and blue (RGB) colour values, homogeneity, and power spectrum density (PSD) features were cross-correlated with the documented spill images. The final crude oil spill Region of Interest (ROI) was determined by grouping interconnected pixels based on their proximity, and only selecting ROIs with an area greater than 5,000 pixels. The crude oil filter cross correlation algorithm demonstrated a sensitivity of 84% with a False Positive per Image (FPI) of 0.82. Future work includes volume estimation of detected spills using crude oil filters, and utilizing this information in the recommendation of appropriate spill clean-up and remediation procedures for the detected spills.

 

http://dx.doi.org/10.4314/njt.v39i2.29

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Published

2020-04-03

Issue

Section

Computer, Telecommunications, Software, Electrical & Electronics Engineering

How to Cite

OIL SPILL IDENTIFICATION IN VISIBLE SENSOR IMAGING USING AUTOMATED CROSS CORRELATION WITH CRUDE OIL IMAGE FILTERS. (2020). Nigerian Journal of Technology, 39(2), 579-588. https://www.nijotech.com/index.php/nijotech/article/view/2311