By Topic

Car license plate recognition with neural networks and fuzzy logic

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 $13
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

7 Author(s)
Nijhuis, J.A.G. ; Dept. of Comput. Sci., Groningen Univ., Netherlands ; ter Brugge, M.H. ; Helmholt, K.A. ; Pluim, J.P.W.
more authors

A car license plate recognition system (CLPR-system) has been developed to identify vehicles by the contents of their license plate for speed-limit enforcement. This type of application puts high demands on the reliability of the CLPR-system. A combination of neural and fuzzy techniques is used to guarantee a very low error rate at an acceptable recognition rate. First experiments along highways in the Netherlands show that the system has an error rate, of 0.02% at a recognition rate of 98.51%. These results are also compared with other published CLPR-systems

Published in:

Neural Networks, 1995. Proceedings., IEEE International Conference on  (Volume:5 )

Date of Conference:

Nov/Dec 1995