DocumentCode :
3330683
Title :
Automatic extraction methods of container identity number and registration plates of cars
Author :
Mullot, R. ; Olivier, C. ; Bourdon, J.L. ; Courtellemont, P. ; Labiche, J. ; Lecourtier, Y.
Author_Institution :
LACIS-ITEPEA, Rouen Univ., Mont-Saint-Aignan, France
fYear :
1991
fDate :
28 Oct-1 Nov 1991
Firstpage :
1739
Abstract :
Three methods of character area localization in noisy images are proposed, constituting the first treatment of automatic recognition of container or wagon identity numbers, or registration plates of cars. The first method, implemented on a two-transputer network, involves a cognitive approach to segmentation, by the search for vertical segments. The second method, based on signal processing, realizes an AR-modeling of the image background, and uses a rupture detection process. The third method is based on the localization of pertinent transitions, i.e. an increase of the gray level crossing over a given percentage of the scale. These methods have been compared on photographs (512×512 pixels on 256 gray levels) of containers and registration plates. The three methods, debugged and checked with the same images, are shown to give good results
Keywords :
computerised pattern recognition; road vehicles; transputers; AR-modeling; cars; cognitive approach; computerised pattern recognition; container identity number; gray level crossing; image background; noisy images; registration plates; road vehicles; rupture detection process; segmentation; signal processing; two-transputer network; vertical segments; wagon identity numbers; Character recognition; Containers; Humans; Image coding; Image recognition; Image segmentation; Parallel architectures; Pixel; Signal processing; Visual system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, Control and Instrumentation, 1991. Proceedings. IECON '91., 1991 International Conference on
Conference_Location :
Kobe
Print_ISBN :
0-87942-688-8
Type :
conf
DOI :
10.1109/IECON.1991.239252
Filename :
239252
Link To Document :
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