Effective horizon detection on complex seas using back propagation neural network

Abstract

Object detection is one of the main features of surface vehicles that do not require a driver (USV). Research on the detection of the horizon is one of the basic factors in conducting obstructions. Precisely detection helps to improve the efficiency and accuracy of object detection. Because it will eliminate most irrelevant areas. In this paper, there are four different algorithms that apply to three image sequences that have been taken in the open sea. This paper focuses on the accuracy rate and efficiency of horizon detection. By testing four different algorithms, including Hough transform, least squares, RANSAC and neural networks to separate the horizon from the image. Experimental results show that artificial neural network methods use more time but accuracy better than others.