Integration of Statistical Methods and Artificial Neural Networks for the Detection of Oil Stains in the Aquatic Environment

Monik Sousa, João Neto

2023

Abstract

The growth in oil exploration and transport increases the risk of accidents in the aquatic environment. Early detection of oil slicks in the aquatic environment is essential to minimize the risk of accidents, as well as effective decision-making. Thus, a method for detecting oil stains is needed to reduce the damage caused by industrial activities to the environment. This article presents statistical methods of classification and machine learning to detect oil slicks on the ocean surface. For this, images from a Synthetic Aperture Radar (SAR) were used. The proposed model for detecting oil slicks uses Linear Discriminant Analysis (LDA) to generate an estimate of the class to which the database images belong (image without oil slick, and image with oil slick), and the Artificial Neural Network (ANN) to classify the data, in which these data come from the grouping of the image with the result of the LDA. With the results obtained, it is concluded that the proposed method of detecting oil slicks on the ocean surface can detect oil slicks with good accuracy.

Paper Citation

in Harvard Style

Sousa M. and Neto J. (2023). Integration of Statistical Methods and Artificial Neural Networks for the Detection of Oil Stains in the Aquatic Environment. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-626-2, pages 550-557. DOI: 10.5220/0011799300003411

in Bibtex Style

@conference{icpram23,
author={Monik Sousa and João Neto},
title={Integration of Statistical Methods and Artificial Neural Networks for the Detection of Oil Stains in the Aquatic Environment},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2023},
pages={550-557},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011799300003411},
isbn={978-989-758-626-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Integration of Statistical Methods and Artificial Neural Networks for the Detection of Oil Stains in the Aquatic Environment
SN - 978-989-758-626-2
AU - Sousa M.
AU - Neto J.
PY - 2023
SP - 550
EP - 557
DO - 10.5220/0011799300003411