Intelligent fouling detection system using haar-like cascade classifier with neural networks

Abstract

Numerous solutions were introduced to combat issues related to marine fouling. But recent studies have shown that the current approach is unable to detect types of fouling on the ships automatically. A fouling detection system using machine learning is therefore proposed. The proposed system incorporates Haar cascade detection with camera module in a waterproof enclosure to detect fouling in real time. The images of barnacles were taken from Singapore’s coastline to train the Haar cascade classifier. The experimental results show that the system can detect the type of barnacle with a reasonable accuracy. The study also includes a fouling repository for users to contribute the fouling images.