This paper presents a powerful automated license plate recognition system, which is able to read license numbers of cars, even under circumstances, which are far from ideal. In a real-life test, the percentage of rejected plates was 13%, whereas 0.4% of the plates were misclassified. Suggestions for further improvements are given.
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