Region proposal for ship detection based on structured forests edge method

Remote sensing images are with the characteristics of large width and sparse distribution of specific targets, so that the extraction of region proposal is necessary before detection. In this paper, we propose a new ship detection method on sea-background remote sensing images, which are generally influenced by clouds, waves and other inhomogeneities. Instead of exhaustive search, the core of our method is that the region proposals are obtained from edge detection based on structured forests, which makes our method accurate and efficient. This edge detection method only demands a small training set and then produces contours with the background suppressed. After some morphological processing on the contours, we obtained ship proposals by connected domain detection. Adopting support vector machine(SVM) as classifier, we finally acquire ship detection results. The remote sensing images in our datasets are downloaded from Google Earth map. In our experiments, the proposed method is feasible and effective, and it shows better performance than other methods especially in various illumination and interference conditions.