Masters Theses
Abstract
"An imaging-processing approach is described that detects the position of a vehicle on a bridge or similar environment. A load-bearing vehicle must be carefully positioned on a bridge for quantitative bridge monitoring. The personnel required for setup and testing and the time required for bridge closure or traffic control are important management and cost considerations. Consequently, bridge monitoring and inspections are good candidates for smart embedded systems. The objectives of this work are to reduce the need for personnel time and to minimize the time for bridge closure. An approach is proposed that uses a passive target on the bridge and camera instrumentation on the load vehicle. The orientation of the vehicle-mounted camera and the target determine the position. The experiment used pre-defined circles as the target, a FireWire camera for image capture, and MATLAB for computer processing. Various image processing techniques are compared for determining the orientation of the target circles with respect to speed and accuracy in the positioning application. The techniques for determining the target orientation use algorithms based on the centroid method, template matching and color of the target object. Timing parameters are determined for each algorithm to determine the feasibility for real-time use in a position triggering system. The development can be combined with embedded sensors and sensor nodes for a complete automated procedure. As the load vehicle moves to the proper position, the image-based system can trigger an embedded measurement which is then transmitted back to the vehicle control computer through a wireless link"--Abstract, page iii.
Advisor(s)
Watkins, Steve Eugene, 1960-
Committee Member(s)
Luechtefeld, Ray
Moss, Randy Hays, 1953-
Department(s)
Electrical and Computer Engineering
Degree Name
M.S. in Electrical Engineering
Publisher
Missouri University of Science and Technology
Publication Date
Summer 2009
Pagination
viii, 75 pages
Rights
© 2009 Amardeep Kaur, All rights reserved.
Document Type
Thesis - Open Access
File Type
text
Language
English
Subject Headings
Bridge failures -- PreventionImage processingMATLABSensor networksSmart structures -- Design and construction
Thesis Number
T 9543
Print OCLC #
471817004
Electronic OCLC #
352886520
Recommended Citation
Kaur, Armadeep, "Vehicle positioning using image processing" (2009). Masters Theses. 6783.
https://scholarsmine.mst.edu/masters_theses/6783