A real-world laboratory exercise is presented for image processing and related curricula. The exercise is a traffic-monitoring problem in which a truck must be tracked as it moves across a bridge and its velocity measured. Sequential images are taken from a dedicated Web camera that views the Smart Composite Bridge on the University of Missouri-Rolla campus. The prototype bridge is a field laboratory for several interdisciplinary courses, including a Machine Vision elective. The Machine Vision image-processing elective uses the traffic-monitoring exercise to give students experience with processing complex images, tracking image markers, and applying theoretical orthographic concepts. The laboratory exercise uses an image sequence acquired during the springtime with multiple potential markers available on the truck for assignment flexibility. A wintertime image sequence with snowy conditions is also available for assignment flexibility. This paper discusses the bridge and camera resources, the traffic-monitoring laboratory exercise description, and the Machine Vision course implementation and evaluation. Two versions of the traffic-monitoring exercise, including two image sequences and orthographic MATLAB code, are available on the bridge Website.
R. J. Stanley et al., "A Web-Shareable Real-World Imaging Problem for Enhancing an Image-Processing Curriculum," IEEE Transactions on Education, vol. 47, no. 2, pp. 211-219, Institute of Electrical and Electronics Engineers (IEEE), May 2004.
The definitive version is available at https://doi.org/10.1109/TE.2004.825214
Electrical and Computer Engineering
Keywords and Phrases
Image Processing; Orthographic Projection; Real-World Educational Laboratory; Traffic Monitoring in Transportation
International Standard Serial Number (ISSN)
Article - Journal
© 2004 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.