Sequence-based Recognition of License Plates with Severe Out-of-Distribution Degradations

Moussa D, Maier A, Schirrmacher F, Rieß C (2021)

Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2021

Publisher: Springer Nature Switzerland AG

Series: Lecture Notes in Computer Science

Book Volume: vol 13053

Pages Range: 175-185

Conference Proceedings Title: Computer Analysis of Images and Patterns

Event location: Virtual Conference CY

ISBN: 978-3-030-89131-2

URI: https://faui1-files.cs.fau.de/public/publications/mmsec/2021-Moussa-SRLP.pdf

DOI: 10.1007/978-3-030-89131-2_16

Open Access Link: https://link.springer.com/content/pdf/10.1007/978-3-030-89131-2_16.pdf

Abstract

Criminal investigations regularly involve the deciphering of license plates (LPs) of vehicles. Unfortunately, the image or video source material typically stems from uncontrolled sources, and may be subject to severe degradations such as extremely low resolution, strong compression, low contrast or over- resp. underexposure. While LP recognition has a long history in computer vision research, the deciphering under such severe degradations is still an open issue. Moreover, since the data source is not controlled, it cannot be assumed that the exact form of degradation is covered in the training set. In this work, we propose using convolutional recurrent neural networks (CRNN) for the recognition of LPs from images with strong unseen degradations. The CRNN clearly outperforms an existing conventional CNN in this scenario. It also provides an additional particular advantage for criminal investigations, namely to create top-n sequence predictions. Even a low number of top-n candidates improves the recognition performance considerably.

Authors with CRIS profile

Denise Moussa Lehrstuhl für Informatik 1 (IT-Sicherheitsinfrastrukturen) Anatol Maier Lehrstuhl für Informatik 1 (IT-Sicherheitsinfrastrukturen) Franziska Schirrmacher Sonderforschungsbereich/Transregio 89 Invasives Rechnen Christian Rieß Lehrstuhl für Informatik 1 (IT-Sicherheitsinfrastrukturen)

How to cite

APA:

Moussa, D., Maier, A., Schirrmacher, F., & Rieß, C. (2021). Sequence-based Recognition of License Plates with Severe Out-of-Distribution Degradations. In Springer, Cham (Eds.), Computer Analysis of Images and Patterns (pp. 175-185). Virtual Conference, CY: Springer Nature Switzerland AG.

MLA:

Moussa, Denise, et al. "Sequence-based Recognition of License Plates with Severe Out-of-Distribution Degradations." Proceedings of the The 19th International Conference on Computer Analysis of Images and Patterns, Virtual Conference Ed. Springer, Cham, Springer Nature Switzerland AG, 2021. 175-185.

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