The Haze Plate Recognition System Based on PSO-RBF Neural Network
[1]Mao Xiaobo,Zhang Qun,Liang Jing,et al.The Haze Plate Recognition System Based on PSO-RBF Neural Network[J].Journal of Zhengzhou University (Engineering Science),2017,38(04):46-50.[doi:10.3969/j.issn.1671-6833.2017.04.002]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
38卷
Number of periods:
2017 04
Page number:
46-50
Column:
Public date:
2017-07-18
- Title:
- The Haze Plate Recognition System Based on PSO-RBF Neural Network
- CLC:
- -
- DOI:
- 10.3969/j.issn.1671-6833.2017.04.002
- Abstract:
- In this paper,a new algorithm of license plate recognition in the hazy weather was designed.Firstly,defogging operation was introduced for license plate image in the environment of hazy by using improved dark channel prior.Then after the pretreatment,positioning,segmentation and extraction,coarse grid characteristic matrix is obtained.Finally,radial basis function (RBF) neural network,which was optimized by particle swarm algorithm in advance,was used to identify the character.The experiment results showed that the improved algorithm not only had a good effect on haze removal,but also reduced the duration of defogging,which effectively improve the license plate recognition speed and accuracy in fog and haze weather.
- References:
- -
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