Abstract
Special features in real marine environments such as cloud clutter, sea glint and weather conditions always result in various kinds of interference in optical images, which make it very difficult for unmanned surface vehicles (USVs) to detect the sea-sky line (SSL) accurately. To solve this problem a saliency-based SSL detection method is proposed. Through the computation of gradient saliency the line features of SSL are enhanced effectively, while other interference factors are relatively suppressed, and line support regions are obtained by a region growing method on gradient orientation. The SSL identification is achieved according to region contrast, line segment length and orientation features, and optimal state estimation of SSL detection is implemented by introducing a cubature Kalman filter (CKF). In the end, the proposed method is tested on a benchmark dataset from the “XL” USV in a real marine environment, and the experimental results demonstrate that the proposed method is significantly superior to other state-of-the-art methods in terms of accuracy rate and real-time performance, and its accuracy and stability are effectively improved by the CKF.
Highlights
In recent years, with their rapid development unmanned surface vehicles (USVs) are playing more and more important roles in various areas such as meteorological monitoring, maritime search and rescue, enemy reconnaissance and precision military strikes
While a distant target enters into the field of view (FOV) of a camera, in optical images it always appears around the sea-sky line (SSL), and moves into the sky region or the sea region during the approaching process, the detection of SSL is an effective measure to improve the target detection, identification and tracking performance through narrowing the target searching range and suppressing false detections
The exposure and focus of method, the “XL” USV was used to acquire optical images of a marine environment in typical the optoelectronic imaging unitweather, were set to auto mode, and the optical image resolution adverse weather like rainy sunny weather with strong illumination, and foggy weather inwas set to Penglai area, Shandong
Summary
With their rapid development USVs are playing more and more important roles in various areas such as meteorological monitoring, maritime search and rescue, enemy reconnaissance and precision military strikes. To navigate autonomously and accomplish a variety of missions without human interventions, USVs need to be equipped with different sensors like radars, cameras and thermal infrared imagers to perceive and comprehend the marine environment and all kinds of targets around them, and intelligent behaviors including target detection, identification and tracking are implemented autonomously. In the optical images obtained by cameras in the marine environment, the sea-sky line (SSL) is one of the most important cues. While a distant target enters into the field of view (FOV) of a camera, in optical images it always appears around the SSL, and moves into the sky region or the sea region during the approaching process, the detection of SSL is an effective measure to improve the target detection, identification and tracking performance through narrowing the target searching range and suppressing false detections. According to the position and motion pattern of the detected SSL, the motion status of USVs can be estimated and Sensors 2016, 16, 543; doi:10.3390/s16040543 www.mdpi.com/journal/sensors
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