A First Approach to Learning a Model of Traffic Signs Using Connectionist and Syntactic Methods
نویسندگان
چکیده
A system to learn and recognize traffic signs is described. The system uses neural network image processing and syntactic methods. The learning process is based on the representation of traffic signs by means of a grammar, which is inferred from a set of positive and negative samples. The recognition of traffic signs in a scene is done in two steps. First, the sign is located in the scene by using a connectionist segmentation method. Second, the sign is coded and analysed to determine which traffic sign it is. The system has been tested successfully only for the first step. The second step is currently under development.
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