A Novel Inshore Ship Detection via Ship Head Classification and Body Boundary Determination
In this letter, we propose a novel method for inshore ship detection via ship head classification and body boundary determination. Compared with some traditional ship head detection methods depending on accurate ship head segmentation, we generate novel ship head features in the transformed domain of polar coordinate, where the ship heads have an approximate trapezoid shape and can be more easily detected. Then, these features are used in the classification based on support vector machine to detect the ship head candidates, and give the important information of initial ship head direction. Next, the surrounding consistent line segments are utilized to refine the ship direction, and the ship boundary is determined based on the saliency of directional gradient information symmetrical about the ship body. Finally, the context information of sea areas is introduced to remove false alarms. Experimental results show that the proposed method can accurately and robustly detect the inshore ships in high-resolution optical remote sensing images.