Unifying Approach for Fast License Plate Localization and Super-Resolution

International audienceThis paper addresses the localization and super-resolutionof license plate in a unifying approach. Higher qualitylicense plate can be obtained using super-resolution onsuccessive lower resolution plate images. All existingmethods assume that plate zones are correctly extractedfrom every frame. However, the accurate localization needsa sufficient quality of the image, which is not always truein real video. Super-resolution on all pixels is a possiblebut much time consuming alternative. We propose a frameworkwhich interlaces successfully these two modules. First,coarse candidates are found by an weak but fast licenseplate detection based on edge map sub-sampling. Then, animproved fast MAP-based super-resolution, using local phaseaccurate registration and edge preserving prior, is appliedon these regions of interest. Finally, our robustICHT-based localizer rejects false-alarms and localizes thehigh resolution license plate more accurately. Experimentswhich were conducted on synthetic and real data, proved therobustness of our approach with real-time possibility