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Super-Resolution of License Plate Images via Character-Based Perceptual Loss
Ist Teil von
2020 IEEE International Conference on Big Data and Smart Computing (BigComp), 2020, p.560-563
Ort / Verlag
IEEE
Erscheinungsjahr
2020
Quelle
IEL
Beschreibungen/Notizen
License Plate Recognition (LPR) is an highly influential problem in computer vision. In this paper, we present a super-resolution model specialized for the license plate images, CSRGAN, trained with a novel character-based perceptual loss. Specifically, we focus on the character-level recognizability of the super-resolved images rather than the pixel-level reconstruction. Experimental results validate the benefits of our proposed method in both quantitative and qualitative aspects. In particular, our method achieves a higher character-level recognition accuracy over the state-of-the-art image super-resolution techniques.