Sea-sky-line detection based on local Otsu segmentation and Hough transform

Due to the interference such as sea waves, ships and light, it is difficult to accurately detect the sea-sky-line of the visible light maritime image. To improve the detection accuracy and robustness, a sea-sky-line detection method based on local Otsu segmentation and Hough transform is proposed. Firstly, high-frequency noise such as light spot in the gray image is rapidly suppressed by longitudinal median filter. Then, according to the image features, the gray image is divided into image blocks in longitudinal to compensate for inhomogeneity of illumination and limit the interference scope of ships to some image blocks. Afterwards, local Otsu segmentation is performed on the gray image to obtain the binary image where edge pixels are extracted, which suppresses the interference of waves. Finally, Hough transform is used to fit edge pixels to complete the sea-sky-line detection. Experimental results show that the proposed method is relatively accurate, robust and real-time. The detection accuracy of the proposed method is 93.0%, which is significantly higher than that of three representative sea-sky-line detection methods.