Title :
Recognition of traffic signs using a multilayer neural network
Author_Institution :
Dept. of Comput. Sci., Memorial Univ. of Newfoundland, St. John´´s, Nfld., Canada
Abstract :
Conventional pattern recognition systems require an input pattern to be presented in a predetermined position. Its orientation and size have to be in such a position for better recognition. However, for a camera in a moving car, the traffic signs may be shifted in position, rotated slightly, or scale changed in relation to the standard position. Furthermore, the traffic signs can be partially occluded and maybe noise-corrupted. Such situations cause lots of difficulties for recognition
Keywords :
edge detection; feedforward neural nets; image recognition; road traffic; image processing; multilayer neural network; noise-corruption; partially occluded signs; pattern recognition systems; standard position; traffic signs recognition; Feedforward neural networks; Image edge analysis; Neural network applications; Pattern recognition;
Conference_Titel :
Electrical and Computer Engineering, 1994. Conference Proceedings. 1994 Canadian Conference on
Conference_Location :
Halifax, NS
Print_ISBN :
0-7803-2416-1
DOI :
10.1109/CCECE.1994.405880
