Next Article in Journal
Exemplar-Based Face Colorization Using Image Morphing
Previous Article in Journal
Computationally Efficient Robust Color Image Watermarking Using Fast Walsh Hadamard Transform
Article Menu
Issue 4 (December) cover image

Export Article

Open AccessArticle
J. Imaging 2017, 3(4), 47; https://doi.org/10.3390/jimaging3040047

Detection and Classification of Land Crude Oil Spills Using Color Segmentation and Texture Analysis

Racett Canada, Inc., 404 St. George Street, Moncton, NB E1C 1X0, Canada
*
Author to whom correspondence should be addressed.
Received: 18 August 2017 / Revised: 9 September 2017 / Accepted: 13 September 2017 / Published: 19 October 2017
Full-Text   |   PDF [6086 KB, uploaded 19 October 2017]   |  

Abstract

Crude oil spills have negative consequences on the economy, environment, health and society in which they occur, and the severity of the consequences depends on how quickly these spills are detected once they begin. Several methods have been employed for spill detection, including real time remote surveillance by flying aircrafts with surveillance teams. Other methods employ various sensors, including visible sensors. This paper presents an algorithm to automatically detect the presence of crude oil spills in images acquired using visible light sensors. Images of crude oil spills used in the development of the algorithm were obtained from the Shell Petroleum Development Company (SPDC) Nigeria website The major steps of the detection algorithm are image preprocessing, crude oil color segmentation, sky elimination segmentation, Region of Interest (ROI) extraction, ROI texture feature extraction, and ROI texture feature analysis and classification. The algorithm was developed using 25 sample images containing crude oil spills and demonstrated a sensitivity of 92% and an FPI of 1.43. The algorithm was further tested on a set of 56 case images and demonstrated a sensitivity of 82% and an FPI of 0.66. This algorithm can be incorporated into spill detection systems that utilize visible sensors for early detection of crude oil spills. View Full-Text
Keywords: crude oil spills; crude oil spill detection; image segmentation; texture feature extraction; automated spill detection crude oil spills; crude oil spill detection; image segmentation; texture feature extraction; automated spill detection
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Ejofodomi, O.; Ofualagba, G. Detection and Classification of Land Crude Oil Spills Using Color Segmentation and Texture Analysis. J. Imaging 2017, 3, 47.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
J. Imaging EISSN 2313-433X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top