Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

You searched for id:"oai:NSYSU:etd-0610117-155210". One record found.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


NSYSU

1. Shiu, Deng-Chau. Positioning of Underwater Towed Vehicles from Image Feature Matching.

Degree: Master, Institute of Undersea Technology, 2017, NSYSU

Underwater navigation is usually achieved by using inertial or acoustic sensors. However, high precision inertial navigation system (INS) is quite expensive and its main drawback is the performance degradation with time. As for the acoustic navigation system, its performance is limited by sound speed variation of the water column, high latency, low refresh rate, and multi-path effect. In additional to inertial and acoustic navigation sensors, optical sensor has a great potential as a navigation tool for underwater vehicles. Considering that video camera is a standard equipment on almost every underwater vehicle, it is easy to collect seafloor videos when a vehicle conducts seafloor survey. With the advantages of high resolution and high frame rate, the seafloor video has a great potential for accurately positioning an underwater vehicle based on detecting and matching image features. Therefore, in this study, we developed a feature-based positioning algorithm for estimating the displacement of underwater vehicles. The feature-based positioning algorithm consists of four steps: radial distortion calibration of the image, attitude calibration of the image plane, the scale invariant feature transform (SIFT) descriptor, and scale transform from image to physical world. To evaluate the performance of the feature-based positioning algorithm, analysis was carried out based on the seafloor videos off southwestern Taiwan collected by using the Fiber-optical Instrumentation Towed System (FITS). The FITS is a deep-towed vehicle that was developed by the National Sun Yat-sen University, which is also equipped with the INS and Doppler velocity log (DVL) for navigation. Measurements of the INS and DVL were also collected while performing seafloor imaging survey. Based on the developed feature-based positioning algorithm, the seafloor images were extracted from the video to detect and match features to estimate the vehicle displacement. Then, the performance of the image feature-based positioning algorithm was evaluated by comparing the estimates of vehicle displacement to the measurements of INS and DVL. Advisors/Committee Members: Chi-Cheng Cheng (chair), Yu-Cheng Chou (chair), Hsin-Hung Chen (committee member).

Subjects/Keywords: FITS; Attitude calibration; SIFT; Towed vehicle; Radial distortion; Feature-based positioning algorithm

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Shiu, D. (2017). Positioning of Underwater Towed Vehicles from Image Feature Matching. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0610117-155210

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Shiu, Deng-Chau. “Positioning of Underwater Towed Vehicles from Image Feature Matching.” 2017. Thesis, NSYSU. Accessed September 24, 2017. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0610117-155210.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Shiu, Deng-Chau. “Positioning of Underwater Towed Vehicles from Image Feature Matching.” 2017. Web. 24 Sep 2017.

Vancouver:

Shiu D. Positioning of Underwater Towed Vehicles from Image Feature Matching. [Internet] [Thesis]. NSYSU; 2017. [cited 2017 Sep 24]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0610117-155210.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shiu D. Positioning of Underwater Towed Vehicles from Image Feature Matching. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0610117-155210

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.