Ideogram identification in a realtime traffic sign recognition system

Abstract

A robust system for the automatic detection of traffic signs has been developed at the Image Recognition Laboratory of the University of Koblenz. This traffic sign recognition (TSR) system was originally designed to localize traffic signs and to recognize their classes, e.g. prohibition signs, danger signs, beacons, etc. The exact identification of traffic signs is added. Traffic signs are identified by the interpretation of their ideograms realized by different modules in our TSR. The first module detects the position and direction of arrows. A second tool recognizes numerals and interprets them as reasonable speed limits. A third one is a general nearest neighbor classifier applied to three classes of ideograms (prohibition sign ideograms, speed limits, arrows on mandatory signs). The fourth module is based on neural nets and applied to two of these classes. Some of these components are used competitively in our realtime TSR. The use of several results from different tools increases the safety and provides high recognition rates.