Unifying Approach for Fast License Plate Localization and Super-Resolution
Résumé
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.