Automatic Recognition of Road Signs in Digital Images for Gis Update

Abstract

Abstract:A method for automatic recognition of road signs identified in digital video images is proposed. The method is based on features extracted from cumulative histograms and supervised classification. The training of the classifier is done with a small number of images (1 to 6) from each sign type. A practical experiment with 260 images and 26 different road sign was carried out. The average classification accuracy of the method with the standard settings was found to be 93.6%. The classification accuracy is improved to 96.2% by accepting the sign types ranked 1 st and 2 nd by the classifier, and to 97.4% by also accepting the sign type ranked 3 rd . These results indicate that this can be a valuable tool to assist Geographic Information System (GIS) updating process based on Mobile Mapping System (MMS) data.