This paper presents a region-based algorithm for accurate license plate localization, where mean shift is utilized to filter and segment color vehicle images into candidate regions. Three features are extracted in order to decide whether a candidate region represents a real license plate, namely, rectangularity, aspect ratio, and edge density. Then, the Mahalanobis classifier is used with respect to above three features to classify license plate regions and non-license plate regions. Experimental results show that the proposed algorithm produces high robustness and accuracy.
Mean shift for accurate license plate localization
2005-01-01
385588 byte
Conference paper
Electronic Resource
English
Mean Shift for Accurate License Plate Localization
British Library Conference Proceedings | 2005
|LICENSE PLATE SHEET, LICENSE PLATE LAMINATE, AND LICENSE PLATE
European Patent Office | 2019
|License plate localization based on a probabilistic model
British Library Online Contents | 2010
|Sheet for license plate, laminate for license plate, and license plate
European Patent Office | 2019
|SHEET FOR LICENSE PLATE, LAMINATE FOR LICENSE PLATE, AND LICENSE PLATE
European Patent Office | 2019
|