This is the first part of a two-part project in which an algorithm system will be set up for detecting and tracking targets in the naval surveillance.
Abstract
This is the first part of a two-part project in which an algorithm system will be set up for detecting and tracking targets in the naval surveillance. The system is intended to facilitate the transformation of the unmanned surface vehicle, the “Protector”, into an autonomic vehicle.
As a pre-process step, before the detection and tracking of the target, we present in this work an algorithm for detecting and aligning the horizon in the panoramic video obtained from the “Protector’s” cameras.
This algorithm is based on the use of Hough Transform for detecting straight lines in the image and on the use of one dimensional correlation for finding the vertical movement of the horizon between two consecutive frames.
The output of this algorithm (i.e. the frame with the aligned horizon) will be the input of the second part of the system in which the target detection and tracking will be performed.
The algorithm has been tested on a wide range of datasets including the panoramic video obtained from the “Protector” and videos taken from the internet. The results show a significant outperformance compared to results achieved in previous works that dealt with the horizon detection issue.
