Comparison of Feature Extractors in License Plate Recognition
AMS '07 Proceedings of the First Asia International Conference on Modelling & Simulation
Detecting, tracking and recognizing license plates
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
A License Plate-Recognition Algorithm for Intelligent Transportation System Applications
IEEE Transactions on Intelligent Transportation Systems
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License plate recognition is done by recognizing the plate in single pictures. The license plate is analyzed in three steps namely the localization of the plate, the segmentation of the characters and the classification of the characters. Temporal redundant information has allready been used to improve the recognition rate, therefore fast algorithms have to be provided to get as many temporal classifications of a moving car as possible. In this paper a fast implementation for single classifications of license plates and performance increasing algorithms for statistical analysis other than a simple majority voting in image sequences are presented. The motivation of using the redundant information in image sequences and therefore classify one car multiple times is to have a more robust and converging classification where wrong single classifications can be suppressed.