ESA-LPD provides a reliable framework for License Plate Detection (LPD) in unconstrained environments. We propose a scale-adaptive deformable part-based model which, based on the GentleBoost algorithm, automatically models scale during the training phase by selecting the most prominent features at each scale and notably reduces the test detection time by avoiding the evaluation at different scales. In addition, our method incorporates an empirically constrained-deformation model that adapts to different levels of deformation shown by distinct local features within license plates.
Code
The code is written in Matlab and includes pre-trained detectors for Spanish, American and Taiwanese license plates.
https://github.com/miguel55/esa-lpd
References
- M. Molina-Moreno, I. González-Díaz and F. Díaz-de-María, “Efficient Scale-Adaptive License Plate Detection System”, IEEE Transactions on Intelligent Transportation Systems (Print ISSN: 1524-9050, Online ISSN: 1558-0016). DOI: 10.1109/TITS.2018.2859035. 2018.