Ultra-Fast Mini License Plate Recognition System Based-on Vision Processing Unit
Pages 14 - 19
Abstract
As more embedded environments need license plate recognition systems, how to recognize car plates with high speed/accuracy and low energy has become an important and challenging problem. In this paper, we propose a ultra-Fast miNi (FaNi) license plate recognition (LPR) system. The FaNi system are divided into one training sub-system and one inference sub-system. The former are used to get some offline features; then, the latter is deployed online to recognize license numbers with nearly real-time speed. The inference system is comprised of the vision processing unit (VPU) and the display unit. These two parts are both implemented with hardware logic. Experiments show that the FaNi system can obtain high accuracy and high speed with low resource cost.
References
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Published In
December 2020
69 pages
ISBN:9781450388399
DOI:10.1145/3440054
Copyright © 2020 ACM.
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Association for Computing Machinery
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Published: 01 February 2021
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BDSIC 2020
BDSIC 2020: 2020 2nd International Conference on Big-data Service and Intelligent Computation
December 3 - 5, 2020
Xiamen, China
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