Super-Resolution Towards License Plate Recognition - Nascimento, Valfride; Laroca, Rayson; Menotti, David (Anais do Concurso de Teses e Dissertações da SBC (CTD-SBC); 2024: Anais do XXXVII Concurso de Teses e DissertaçõesDO - 10.5753/ctd.2024.1999, 2024)
Recent years have seen significant developments in license plate recognition through the integration of deep learning techniques and the increasing availability of training data. Nevertheless, reconstructing license plates from low-resolution surveillance footage remains a challenge. To address this issue, we propose an attention-based super-resolution approach that incorporates sub-pixel convolution layers and an Optical Character Recognition (OCR)-based loss function. We trained the proposed architecture using synthetic images created by applying heavy Gaussian noise followed by bicubic downsampling to high-resolution license plate images. Our results show that the proposed approach for reconstructing these low-resolution images substantially outperforms existing methods in both quantitative and qualitative measures. Our source code is publicly available at https://github.com/valfride/lpr-rsr-ext/ .