Forensic License Plate Recognition with Compression-Informed Transformers

Moussa D, Maier A, Spruck A, Seiler J, Rieß C (2022)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2022

Publisher: IEEE

Pages Range: 406-410

Conference Proceedings Title: 2022 IEEE International Conference on Image Processing (ICIP)

Event location: Bordeaux, France FR

ISBN: 978-1-6654-9620-9

URI: https://faui1-files.cs.fau.de/public/publications/mmsec/2022-Moussa-FLPR.pdf

DOI: 10.1109/ICIP46576.2022.9897178

Open Access Link: https://faui1-files.cs.fau.de/public/publications/mmsec/2022-Moussa-FLPR.pdf

Abstract

Forensic license plate recognition (FLPR) remains an open challenge in legal contexts such as criminal investigations, where unreadable license plates (LPs) need to be deciphered from highly compressed and/or low resolution footage, e.g., from surveillance cameras. In this work, we propose a side-informed Transformer architecture that embeds knowledge on the input compression level to improve recognition under strong compression. We show the effectiveness of Transformers for license plate recognition (LPR) on a low-quality real-world dataset. We also provide a synthetic dataset that includes strongly degraded, illegible LP images and analyze the impact of knowledge embedding on it. The network outperforms existing FLPR methods and standard state-of-the art image recognition models while requiring less parameters. For the severest degraded
images, we can improve recognition by up to 8.9 percent points.

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How to cite

APA:

Moussa, D., Maier, A., Spruck, A., Seiler, J., & Rieß, C. (2022). Forensic License Plate Recognition with Compression-Informed Transformers. In IEEE (Eds.), 2022 IEEE International Conference on Image Processing (ICIP) (pp. 406-410). Bordeaux, France, FR: IEEE.

MLA:

Moussa, Denise, et al. "Forensic License Plate Recognition with Compression-Informed Transformers." Proceedings of the IEEE International Conference on Image Processing, Bordeaux, France Ed. IEEE, IEEE, 2022. 406-410.

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