Academic Journal
Ship Ranging Method in Lake Areas Based on Binocular Vision.
| Τίτλος: | Ship Ranging Method in Lake Areas Based on Binocular Vision. |
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| Συγγραφείς: | Zhang, Tengwen, Liu, Xin, Shao, Mingzhi, Sun, Yuhan, Zhang, Qingfa |
| Πηγή: | Sensors (14248220); Oct2025, Vol. 25 Issue 20, p6477, 21p |
| Θεματικοί όροι: | Binocular vision, Stereo vision (Computer science), Triangulation, Navigation, Object recognition (Computer vision), Lakes |
| Περίληψη: | The unique hollowed-out catamaran hulls and complex environmental conditions in lake areas hinder traditional ranging algorithms (combining target detection and stereo matching) from accurately obtaining depth information near the center of ships. This not only impairs the navigation of electric tourist boats but also leads to high computing resource consumption. To address this issue, this study proposes a ranging method integrating improved ORB (Oriented FAST and Rotated BRIEF) with stereo vision technology. Combined with traditional optimization techniques, the proposed method calculates target distance and angle based on the triangulation principle, providing a rough alternative solution for the "gap period" of stereo matching-based ranging. The method proceeds as follows: first, it acquires ORB feature points with relatively uniform global distribution from preprocessed binocular images via a local feature weighting approach; second, it further refines feature points within the ROI (Region of Interest) using a quadtree structure; third, it enhances matching accuracy by integrating the FLANN (Fast Library for Approximate Nearest Neighbors) and PROSAC (Progressive Sample Consensus) algorithms; finally, it applies the screened matching point pairs to the triangulation method to obtain the position and distance of the target ship. Experimental results show that the proposed algorithm improves processing speed by 6.5% compared with the ORB-PROSAC algorithm. Under ideal conditions, the ranging errors at 10m and 20m are 2.25% and 5.56%, respectively. This method can partially compensate for the shortcomings of stereo matching in ranging under the specified lake area scenario. [ABSTRACT FROM AUTHOR] |
| Copyright of Sensors (14248220) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Ship Ranging Method in Lake Areas Based on Binocular Vision. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Tengwen%22">Zhang, Tengwen</searchLink><br /><searchLink fieldCode="AR" term="%22Liu%2C+Xin%22">Liu, Xin</searchLink><br /><searchLink fieldCode="AR" term="%22Shao%2C+Mingzhi%22">Shao, Mingzhi</searchLink><br /><searchLink fieldCode="AR" term="%22Sun%2C+Yuhan%22">Sun, Yuhan</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Qingfa%22">Zhang, Qingfa</searchLink> – Name: TitleSource Label: Source Group: Src Data: Sensors (14248220); Oct2025, Vol. 25 Issue 20, p6477, 21p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Binocular+vision%22">Binocular vision</searchLink><br /><searchLink fieldCode="DE" term="%22Stereo+vision+%28Computer+science%29%22">Stereo vision (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Triangulation%22">Triangulation</searchLink><br /><searchLink fieldCode="DE" term="%22Navigation%22">Navigation</searchLink><br /><searchLink fieldCode="DE" term="%22Object+recognition+%28Computer+vision%29%22">Object recognition (Computer vision)</searchLink><br /><searchLink fieldCode="DE" term="%22Lakes%22">Lakes</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The unique hollowed-out catamaran hulls and complex environmental conditions in lake areas hinder traditional ranging algorithms (combining target detection and stereo matching) from accurately obtaining depth information near the center of ships. This not only impairs the navigation of electric tourist boats but also leads to high computing resource consumption. To address this issue, this study proposes a ranging method integrating improved ORB (Oriented FAST and Rotated BRIEF) with stereo vision technology. Combined with traditional optimization techniques, the proposed method calculates target distance and angle based on the triangulation principle, providing a rough alternative solution for the "gap period" of stereo matching-based ranging. The method proceeds as follows: first, it acquires ORB feature points with relatively uniform global distribution from preprocessed binocular images via a local feature weighting approach; second, it further refines feature points within the ROI (Region of Interest) using a quadtree structure; third, it enhances matching accuracy by integrating the FLANN (Fast Library for Approximate Nearest Neighbors) and PROSAC (Progressive Sample Consensus) algorithms; finally, it applies the screened matching point pairs to the triangulation method to obtain the position and distance of the target ship. Experimental results show that the proposed algorithm improves processing speed by 6.5% compared with the ORB-PROSAC algorithm. Under ideal conditions, the ranging errors at 10m and 20m are 2.25% and 5.56%, respectively. This method can partially compensate for the shortcomings of stereo matching in ranging under the specified lake area scenario. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Sensors (14248220) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/s25206477 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 6477 Subjects: – SubjectFull: Binocular vision Type: general – SubjectFull: Stereo vision (Computer science) Type: general – SubjectFull: Triangulation Type: general – SubjectFull: Navigation Type: general – SubjectFull: Object recognition (Computer vision) Type: general – SubjectFull: Lakes Type: general Titles: – TitleFull: Ship Ranging Method in Lake Areas Based on Binocular Vision. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhang, Tengwen – PersonEntity: Name: NameFull: Liu, Xin – PersonEntity: Name: NameFull: Shao, Mingzhi – PersonEntity: Name: NameFull: Sun, Yuhan – PersonEntity: Name: NameFull: Zhang, Qingfa IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 14248220 Numbering: – Type: volume Value: 25 – Type: issue Value: 20 Titles: – TitleFull: Sensors (14248220) Type: main |
| ResultId | 1 |