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Open Computer Science

Editor-in-Chief: van den Broek, Egon

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CiteScore 2018: 0.63
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ICV 2018: 97.86

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Feature extraction for license plate location based on L0-norm smoothing

Junqing Huang / Michael Ruzhanshy
  • University of Ghent, Belgium; Queen Mary; University of London, UK; Department of Mathematics, Imperial College London, UKLondon
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/ Haoxiang Feng / Lingfang Zheng / Xin Huang / Haihui Wang
Published Online: 2019-06-25 | DOI: https://doi.org/10.1515/comp-2019-0007


We propose a simple feature extraction algorithm for license plate location, which can reduce the occurrence of pseudo-licenses significantly. Our scheme arises from a novel L0-norm image smoothing, in which the multiple local textures in the complex backgrounds can be suppressed remarkably without changing the structures and edges of the license objects. Due to this “edgeaware” property, we then combine a feature filtering with an efficient binarized image, a simple multi-scale image analysis algorithm, to remove the potential false license plates. Finally, we extract license plates with a projection method. Experimental results show the proposed method provides a flexible and powerful way to the license plate location in complex backgrounds.

Keywords: license plate location; L0-norm minimization; feature filtering; binarized image


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About the article

Received: 2018-07-10

Accepted: 2019-05-16

Published Online: 2019-06-25

Citation Information: Open Computer Science, Volume 9, Issue 1, Pages 128–135, ISSN (Online) 2299-1093, DOI: https://doi.org/10.1515/comp-2019-0007.

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© 2019 Junqing Huang et al., published by De Gruyter Open. This work is licensed under the Creative Commons Attribution 4.0 Public License. BY 4.0

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