A Character Recognition Method for License Plate Based on Combination Feature and Partial Character Input

DOI

10.2991/cecs-18.2018.18How to use a DOI?

Keywords

License plate character recognition, LBP feature, projection feature, BP neural network.

Abstract

In order to improve the recognition rate of license plate characters, a new method based on combination feature and partial character input is proposed. First, according to the texture characteristics of the license plate character, the basic LBP operator is improved, and then the characteristics of the license plate partial character image are extracted using the improved local binary mode and horizontal vertical projection, and the classifier is trained with the extracted features. Then use this classifier to classify and identify license plate characters. The experimental results show that the overall recognition rate of license plate reaches 94.56 %, which proves the effectiveness and robustness of this method.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qiang Li
AU  - Juan Zhang
PY  - 2018/07
DA  - 2018/07
TI  - A Character Recognition Method for License Plate Based on Combination Feature and Partial Character Input
BT  - Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)
PB  - Atlantis Press
SP  - 94
EP  - 98
SN  - 2352-538X
UR  - https://doi.org/10.2991/cecs-18.2018.18
DO  - 10.2991/cecs-18.2018.18
ID  - Li2018/07
ER  -