Title :
Car license plate recognition with neural networks and fuzzy logic
Author :
Nijhuis, J.A.G. ; ter Brugge, M.H. ; Helmholt, K.A. ; Pluim, J.P.W. ; Spaanenburg, L. ; Venema, R.S. ; Westenberg, M.A.
Author_Institution :
Dept. of Comput. Sci., Groningen Univ., Netherlands
Abstract :
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
Keywords :
fuzzy logic; image segmentation; neural nets; optical character recognition; Netherlands; car license plate recognition; fuzzy logic; neural networks; speed-limit enforcement; very low error rate; Character recognition; Error analysis; Fasteners; Fuzzy logic; Image segmentation; Licenses; Neural networks; Optical character recognition software; Pixel; Vehicles;
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
DOI :
10.1109/ICNN.1995.487708
