License Plate Recognition Using MSER and HOG Based on ELM
Gou C(苟超); Wang KF(王坤峰); Zhongdong Yu; Haitao Xie
2014
Conference NameIEEE International Conference on Service Operations and Logistics, and Informatics
Conference Date2014
Conference PlaceQingdao
AbstractIn this paper, an effective method for automatic license plate recognition (ALPR) is proposed, on the basis of extreme learning machine (ELM). Firstly, morphological TopHat filtering operator is applied to do the image pre-processing. Then candidate character regions are extracted by means of maximally stable extremal region (MSER) detector. Thirdly, most of the noise character regions are removed according to the geometrical relationship of characters in standard license plates. Finally, the histograms of oriented gradients (HOG) features are extracted from each character of every plate detected and the characters are recognized by the classifier trained through the ELM. Experimental evaluation shows that our approach significantly performs well in the ALPR systems.
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14756
Collection复杂系统管理与控制国家重点实验室_先进控制与自动化
Recommended Citation
GB/T 7714
Gou C,Wang KF,Zhongdong Yu,et al. License Plate Recognition Using MSER and HOG Based on ELM[C],2014.
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