Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Real-time image processing approach to measure traffic queue parameters

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Fathy, M. ; Dept. of Comput. Eng., Iran Univ. of Sci. & Technol., Tehran, Iran ; Siyal, M.Y.

The real-time measurement of various traffic parameters including queue parameters is required in many traffic situations such as accident and congestion monitoring and adjusting the timings of the traffic lights. In case of the queue detection, at least two algorithms have been proposed by previous researchers. Those algorithms are used for queue detection and are unable to measure queue parameters. The authors propose a method based on applying the combination of noise insensitive and simple algorithms on a number of sub-profiles (a one-pixel-wide key-region) along the road. The proposed queue detection algorithm consists of motion detection and vehicle detection operations, both based on extracting edges of the scene, to reduce the effects of variation of lighting conditions. To reduce the computation time, the motion detection operation continuously operates on all the sub-profiles, but the vehicle detection is only applied to the tail of the queue. The proposed algorithms have been implemented on an 80386-based microcomputer system and the whole system works in real-time

Published in:

Vision, Image and Signal Processing, IEE Proceedings -  (Volume:142 ,  Issue: 5 )