A fast recognition algorithm of ship hatch in bulk cargo terminal based on point cloud contour extraction. (January 2023)
- Record Type:
- Journal Article
- Title:
- A fast recognition algorithm of ship hatch in bulk cargo terminal based on point cloud contour extraction. (January 2023)
- Main Title:
- A fast recognition algorithm of ship hatch in bulk cargo terminal based on point cloud contour extraction
- Authors:
- Li, Yuan
Li, Zhan
Yang, Yipeng
Zhao, Lijun
Yang, Liu - Abstract:
- Port loading automation systems can improve the efficiency of cargo transfer, save port operation time and create greater economic benefits. The recognition of ship hatch is the basis and premise of building an automatic loading system, it is a major time cost in the loading system meanwhile. How to identify the hatch quickly and accurately is an important problem that needs to be solved urgently under the actual production needs of ports. In order to save the time of ship hatch recognition, this paper proposes a fast hatch recognition algorithm based on point cloud contour extraction. The ship point cloud model generated by lidar scanning is preprocessed to remove the noise and isolated points in the model. Projecting the preprocessed point cloud on the XOY plane, converting the three-dimensional point cloud into a two-dimensional image, extracting the outline further getting the point cloud pixels with linear features of the two-dimensional image byα − shape algorithm. Projecting the feature point cloud to the X-axis to classify the hatches. According to the center point of each class of point cloud, searching for the nearest neighbor hatch edge feature points to calculate hatch coordinates in the world frame. An experimental study was carried out on the scan data of actual docked ships at Guoneng Tianjin Port. The results show that the algorithm can realize the hatch recognition quickly which the speed is increased by 424% compared with the previous algorithm and thePort loading automation systems can improve the efficiency of cargo transfer, save port operation time and create greater economic benefits. The recognition of ship hatch is the basis and premise of building an automatic loading system, it is a major time cost in the loading system meanwhile. How to identify the hatch quickly and accurately is an important problem that needs to be solved urgently under the actual production needs of ports. In order to save the time of ship hatch recognition, this paper proposes a fast hatch recognition algorithm based on point cloud contour extraction. The ship point cloud model generated by lidar scanning is preprocessed to remove the noise and isolated points in the model. Projecting the preprocessed point cloud on the XOY plane, converting the three-dimensional point cloud into a two-dimensional image, extracting the outline further getting the point cloud pixels with linear features of the two-dimensional image byα − shape algorithm. Projecting the feature point cloud to the X-axis to classify the hatches. According to the center point of each class of point cloud, searching for the nearest neighbor hatch edge feature points to calculate hatch coordinates in the world frame. An experimental study was carried out on the scan data of actual docked ships at Guoneng Tianjin Port. The results show that the algorithm can realize the hatch recognition quickly which the speed is increased by 424% compared with the previous algorithm and the identification accuracy meets the actual production needs of the port. … (more)
- Is Part Of:
- Measurement and control. Volume 56:Number 1/2(2023)
- Journal:
- Measurement and control
- Issue:
- Volume 56:Number 1/2(2023)
- Issue Display:
- Volume 56, Issue 1/2 (2023)
- Year:
- 2023
- Volume:
- 56
- Issue:
- 1/2
- Issue Sort Value:
- 2023-0056-NaN-0000
- Page Start:
- 228
- Page End:
- 236
- Publication Date:
- 2023-01
- Subjects:
- port loading automation -- ship hatch recognition -- plane projection -- point cloud contour extraction -- α—shape
Automatic control -- Periodicals
Engineering instruments -- Periodicals
Production engineering -- Periodicals
629.8 - Journal URLs:
- http://mac.sagepub.com ↗
http://www.uk.sagepub.com/home.nav ↗
http://catalog.hathitrust.org/api/volumes/oclc/4518800.html ↗ - DOI:
- 10.1177/00202940221090967 ↗
- Languages:
- English
- ISSNs:
- 0020-2940
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24857.xml