Abstract
License-plate location in sensor images plays an important role in vehicle identification for automated transport systems (ATS). This paper presents a novel method based on vector quantization (VQ) to process vehicle images. The proposed method makes it possible to perform superior picture compression for archival purposes and to support effective location at the same time. As compared with classical approaches, VQ encoding can give some hints about the contents of image regions; such additional information can be exploited to boost location performance. The VQ system can be trained by way of examples; this gives the advantages of adaptiveness and on-field tuning. The approach has been tested in a real industrial application and included satisfactorily in a complete ATS for vehicle identification.
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