The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
License Plate Recognition From Still Images and Video Sequences: A Survey
Open accessAbstract
License plate recognition (LPR) algorithms in images or videos are generally composed of the following three processing steps: 1) extraction of a license plate region; 2) segmentation of the plate characters; and 3) recognition of each character. This task is quite challenging due to the diversity of plate formats and the nonuniform outdoor illumination conditions during image acquisition. Therefore, most approaches work only under restricted conditions such as fixed illumination, limited vehicle speed, designated routes, and stationary backgrounds. Numerous techniques have been developed for LPR in still images or video sequences, and the purpose of this paper is to categorize and assess them. Issues such as processing time, computational power, and recognition rate are also addressed, when available. Finally, this paper offers to researchers a link to a public image database to define a common reference point for LPR algorithmic assessment.
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Data-Driven Intelligent Transportation Systems: A Survey
Zhang, J., Wang, F.-Y., Wang, K., Lin, W.-H., Xu, X., & Chen, C. (2011) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2011.2158001 · Cited by 1,817
Automatic License Plate Recognition (ALPR): A State-of-the-Art Review
Du, S., Ibrahim, M., Shehata, M., & Badawy, W. (2013) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2012.2203741 · Cited by 835
NoScope: optimizing neural network queries over video at scale
Kang, D., Emmons, J., Abuzaid, F., Bailis, P., & Zaharia, M. (2017) · Proceedings of the VLDB Endowment · doi:10.14778/3137628.3137664 · Cited by 367
50 Years of object recognition: Directions forward
Andreopoulos, A., & Tsotsos, J. K. (2013) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2013.04.005 · Cited by 347
LAVEA: latency-aware video analytics on edge computing platform
Yi, S., Hao, Z., Zhang, Q., Zhang, Q., Shi, W., & Li, Q. (2017) · Proceedings of the Second ACM/IEEE Symposium on Edge Computing · doi:10.1145/3132211.3134459 · Cited by 244
Metadata
- Authors
- Anagnostopoulos, C.-N. E., Anagnostopoulos, I. E., Psoroulas, I. D., Loumos, V., & Kayafas, E.
- Venue
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2008-09
- Volume
- 9
- Issue
- 3
- Pages
- 377-391
- ISSN
- 1524-9050 (ISSN-L)
- 1558-0016
- OpenAlex
- W2135449683
- Cited by
- 645
- References
- 7
- FWCI
- 74.13
- Type
- journal article
- Language
- en
- Open access
- green
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- Anagnostopoulos, C.-N. E., Anagnostopoulos, I. E., Psoroulas, I. D., Loumos, V., & Kayafas, E. (2008). License Plate Recognition From Still Images and Video Sequences: A Survey. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/tits.2008.922938
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