Accurate detection of berthing ship target based on mask R-CNN

Yu Zhang; Yan Zhang; Shu-Xin Li; Jing-Hua Zhang

doi:10.1117/12.2326820

29 October 2018 Accurate detection of berthing ship target based on mask R-CNN

Yu Zhang, Yan Zhang, Shu-Xin Li, Jing-Hua Zhang

Proceedings Volume 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence; 1083602 (2018) https://doi.org/10.1117/12.2326820
Event: 2018 International Conference on Image, Video Processing and Artificial Intelligence, 2018, Shanghai, China

Abstract

This paper mainly studies the berthing ship target detection method of overhead-view image under the condition of a few training samples. Because of the limited training samples, we use the complete data set unrelated to the target detection task for pre-training to obtain a classification model, then expand the data according to a certain percentage and finally complete the training of the target detection model. This paper uses the idea of segmentation to solve the target detection problem. We adjusted the configuration of the region proposal network including the size of anchor frame and the threshold of non-maximum suppression according to the target morphology, so that the network generates a more accurate region of interest. Finally, the confidence levels, bounding-boxes and image masks of multi-objective generated concurrently. We performed experiments on self-made data sets which labeled from NWPU VHR-10 and produced good results, which proved the feasibility of this method in target detection of berthing ship target.

Citation Download Citation

Yu Zhang, Yan Zhang, Shu-Xin Li, and Jing-Hua Zhang "Accurate detection of berthing ship target based on mask R-CNN", Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 1083602 (29 October 2018); https://doi.org/10.1117/12.2326820

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