SHIP target image recognition based on FAST detector and faster-RCNN

This article proposes a ship target recognition method based on FAST detector and Faster-RCNN. Firstly, the FAST detector is used to extract the feature points of the ship target. Then, using the method of increasing the sliding window, improving the convolutional layer structure of Faster R-CNN, using suitable anchor points to identify the target; designed a recognition method based on the combination of the real-world model identification frame and the area suggestion to obtain the target information. Finally, the method of non-maximum suppression is used to filter and remove the redundant rectangular identification frame, so as to realize the accurate identification of the ship's real-world target. Through experimental comparison and analysis, this method has application advantages in extracting feature points with greater recognition utility and recognition rate.