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Vector quantization for license-plate location and image coding

机译:用于车牌定位和图像编码的矢量量化

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摘要

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.
机译:传感器图像中的车牌位置在自动运输系统(ATS)的车辆识别中起着重要作用。本文提出了一种基于矢量量化(VQ)的新方法来处理车辆图像。所提出的方法使得可以出于存档目的执行出色的图片压缩并且同时支持有效的位置。与传统方法相比,VQ编码可以为图像区域的内容提供一些提示。可以利用此类附加信息来提高位置性能。 VQ系统可以通过示例进行训练;这提供了自适应和现场调整的优势。该方法已经在实际的工业应用中进行了测试,并且令人满意地包含在用于车辆识别的完整ATS中。

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