Abstract

The paper proposes a solution to the problem of detecting oil pollution on a monochrome radar image. The detection of oil pollution in the image includes the solution of three tasks: detecting a dark object on the image, highlighting the main characteristics of a dark object, classifying a dark object as oil pollution or natural slick. Various characteristics of a dark object are proposed based on the contrast between the object and the background. It is proposed to use a neural network as a classifier. The input parameters of the neural network classifier of the dark image object are proposed. A technique for determining the structure of a neural classifier is presented. An algorithm for testing the selected structure of the neural network for the suitability of classifying the dark area on the image of the water surface as oil pollution or wind slick is proposed. The results of the work of the neural network classifier program for detecting abnormal objects in radar images are demonstrated.

Highlights

  • The paper proposes a neural network (NN) classifier, which is used in the processing of radar images (RI) of the sea surface

  • ─ a dark object has a high contrast compared to the surrounding background; ─ the surrounding background is homogeneous; ─ wind speed is in the range from 6 to 10 m/s; ─ oil tanker or drilling platform directly connected to a dark object

  • ─ wind speed is in the range from 3 to 6 m/s; ─ a dark object has a low contrast to the gray level that determines the surrounding background, especially at wind speeds from 6 to 10 m/s; ─ the shape of the dark object is asymmetric, i.e. rough edges

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Summary

Introduction

The paper proposes a neural network (NN) classifier, which is used in the processing of radar images (RI) of the sea surface. The classifier identifies a dark object on the radar and detects it as an oil slick or wind slick [1]. The presence of an oil film on the surface of the sea reduces small waves due to the increasing viscosity of the upper layer and significantly reduces the energy of backscattering of the signal, dark regions appear on the radar images [2]. Blackouts in the image can occur due to local low-speed winds above the sea surface or the presence of natural sea slicks.

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