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

Leyuan Zhao; Bihui Liu; Chuanhui Liu

doi:10.1117/12.2604529

5 October 2021 SHIP target image recognition based on FAST detector and faster-RCNN

Leyuan Zhao, Bihui Liu, Chuanhui Liu

Proceedings Volume 11911, 2nd International Conference on Computer Vision, Image, and Deep Learning; 1191116 (2021) https://doi.org/10.1117/12.2604529
Event: 2nd International Conference on Computer Vision, Image and Deep Learning, 2021, Liuzhou, China

Abstract

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.

Citation Download Citation

Leyuan Zhao, Bihui Liu, and Chuanhui Liu "SHIP target image recognition based on FAST detector and faster-RCNN", Proc. SPIE 11911, 2nd International Conference on Computer Vision, Image, and Deep Learning, 1191116 (5 October 2021); https://doi.org/10.1117/12.2604529

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