The real-time reliable detection of the horizon line on high-resolution maritime images for unmanned surface-vehicle

Horizon detection is useful in maritime image processing for various purposes, such as spatial orientation estimation of ship camera and detection of the significant region for post-processing. This paper proposed a novel realtime optimization-based method for detecting the horizon line in maritime images. Traditional methods defined the horizon line detection problem aim to detect the horizon line which perfectly divides the whole image into two regions as the sky and sea. Thus, the complication of traditional methods is the statistical distance metrics of distributions are calculated in the whole image by all combinations of the horizon line parameters. Moreover, traditional methods do not provide realtime processing to detect the horizon line from high-resolution images. To achieve real-time processing on high-resolution images, this study defines the local features of the horizon line using a vanishing line characteristic and the optimization criteria. In addition, the optimization process is improved by combining a genetic algorithm and a coarse-to-fine approach. Our method applied the Singapore marine dataset and the Buoy dataset. To verify the proposed method, our result is compared to the state of the art methods. We confirm the proposed method can accurately detect the horizon line under different scenarios in real-time.