A Novel Algorithm for Ship Detection Based on Dynamic Fusion Model of Multi-feature and Support Vector Machine

Ship detection is one of the most important applications of target recognition based on optical remote sensing images. In this paper, we propose an uncertain ship target extraction algorithm based on dynamic fusion model of multi-feature and variance feature of optical remote sensing image. We choose several geometrical features, such as length, wide, rectangular ratio, tightness ratio and so on, using SVM to train and predict the uncertain ship targets extracted by our algorithm automatically. Experiments show that our algorithm is very robust, and the recognition rate of our algorithm can reach or even better than 95%, with the false alarm rate is kept at 3%.