Robust license plate segmentation method based on texture features and radon transform
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
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The paper describes a novel approach using vector quantization (VQ) to process vehicle images for automated identification. The VQ-based method yields superior quality in picture compression for archival purposes, and, at the same time, supports the localization of text regions in the image effectively. As opposed to standard approaches, VQ encoding gives some hint about the contents of image regions; such information is exploited to boost localization performance. The VQ system may be trained empirically from examples; this provides adaptiveness and on-field tuning facility. The approach has been tested in a real application and included satisfactorily into a complete system for vehicle identification.