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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

Traffic Sign Classification Base on Latent Dirichlet Allocation

verfasst von : Lei Song, Zheyuan Liu, Xiaoteng Zhang, Huixian Duan, Na Liu, Jie Dai

Erschienen in: Frontier Computing

Verlag: Springer Singapore

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Abstract

Traffic sign classification is a significant issue in the intelligent vehicle domain, which helps vehicles to follow the traffic rules and ensure the safety. Feature selection and description are very important and difficult for classification. In this paper, a novel traffic sign classification method is proposed which is based on the Latent Dirichlet Allocation (LDA) model. Feature topics are modeled based on various traffic signs by the LDA automatically. And traffic signs captured onboard are classified according to the modeled features. The experiment results show the efficiency of our work.

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Metadaten
Titel
Traffic Sign Classification Base on Latent Dirichlet Allocation
verfasst von
Lei Song
Zheyuan Liu
Xiaoteng Zhang
Huixian Duan
Na Liu
Jie Dai
Copyright-Jahr
2018
Verlag
Springer Singapore
Buch
Frontier Computing

Print ISBN: 978-981-10-7397-7

Electronic ISBN: 978-981-10-7398-4

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-981-10-7398-4_12

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