Unifying Approach for Fast License Plate Localization and Super-Resolution

Chu Duc Nguyen 1 Mohsen Ardabilian 1 Liming Chen 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : This paper addresses the localization and super-resolution of license plate in a unifying approach. Higher quality license plate can be obtained using super-resolution on successive lower resolution plate images. All existing methods assume that plate zones are correctly extracted from every frame. However, the accurate localization needs a sufficient quality of the image, which is not always true in real video. Super-resolution on all pixels is a possible but much time consuming alternative. We propose a framework which interlaces successfully these two modules. First, coarse candidates are found by an weak but fast license plate detection based on edge map sub-sampling. Then, an improved fast MAP-based super-resolution, using local phase accurate registration and edge preserving prior, is applied on these regions of interest. Finally, our robust ICHT-based localizer rejects false-alarms and localizes the high resolution license plate more accurately. Experiments which were conducted on synthetic and real data, proved the robustness of our approach with real-time possibility.
Type de document :
Communication dans un congrès
20th International Conference on Pattern Recognition (ICPR), Aug 2010, Istanbul, Turkey. IEEE, pp.376-379, 2010, 〈10.1109/ICPR.2010.100〉
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https://hal.archives-ouvertes.fr/hal-01381469
Contributeur : Équipe Gestionnaire Des Publications Si Liris <>
Soumis le : vendredi 14 octobre 2016 - 14:46:20
Dernière modification le : vendredi 10 novembre 2017 - 01:18:17

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Chu Duc Nguyen, Mohsen Ardabilian, Liming Chen. Unifying Approach for Fast License Plate Localization and Super-Resolution. 20th International Conference on Pattern Recognition (ICPR), Aug 2010, Istanbul, Turkey. IEEE, pp.376-379, 2010, 〈10.1109/ICPR.2010.100〉. 〈hal-01381469〉

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