Dynamic Identification of Ship Waterline Image Area Based on Knowledge Guidance
[1]Cheng Jian,An Hongbo,Guo Yinan,et al.Dynamic Identification of Ship Waterline Image Area Based on Knowledge Guidance[J].Journal of Zhengzhou University (Engineering Science),2021,42(03):47-.[doi:10.13705/j.issn.1671-6833.2021.03.008]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
42卷
Number of periods:
2021 03
Page number:
47-
Column:
Public date:
2021-05-10
- Title:
- Dynamic Identification of Ship Waterline Image Area Based on Knowledge Guidance
- Keywords:
- aerial image; waterline area; statistic-based selection for contour; knowledge guidance; dynamic identification
- CLC:
- -
- DOI:
- 10.13705/j.issn.1671-6833.2021.03.008
- Abstract:
- In traditional image-based waterline identification method, a fixed camera is used to capture the waterline area, which requires complex equipments and has difficulty to measure the waterline of the outer chord of ships. This will decrease the identification efficiency. Based on this, a dynamic identification method of waterline area based on aerial image captured by UAV is proposed. Though UAV is more convenient than the fixed cameras, the waterline area in the images may be unsettled due to the unstable flight track. In addition, water trace, ripples in the surface of water and different exposure environment all have the adverse impact on the recognition of waterline. Thus, a statistic-based selection for contour combined with the prior knowledge of waterline characteristics is adopted to locate the interesting horizontal areas containing the waterline. After comprehensively utilizing the color and spatial information of pixels, the waterline is accurately segmented by knowledge-guided K-means++ and watershed algorithm under L×a×b color space. The experimental results show that the proposed method can effectively process the influence from light conditions, water traces and so on, as well as rapidly identify the waterline area from a dynamic video. Its strong robustness for the complex environment in ports provides the foundation for obtaining the accurate weigh of cargoes.
- References:
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Last Update:
2021-06-24