中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
License Plate Localization With Efficient Markov Chain Monte Carlo

文献类型:会议论文

作者Lijun, Cao; Xu, Zhang; Weihua, Chen; Kaiqi, Huang
出版日期2014-06
会议日期2014-6
会议地点厦门
关键词License Plate Localization Feature Likelihood Mcmc Proposal Probability
英文摘要This paper presents a novel efficient Markov Chain Monte
Carlo (MCMC) method for License Plate (LP) localization.
The proposed method formulates the LP image feature and
prior knowledge into a unified Bayesian framework. Then
the localization problem is derived as a maximizing-a-posterior
(MAP) problem, which integrates color, edge and character
feature of LP. We propose an efficient MCMC method,
taking integrated local geometrical likelihood as proposal
probability to make the inference feasible. The experimental
results on real dataset are very promising in terms of
detection rate and localization accuracy.
会议录Proceeding of International Conference on Internet Multimedia Computing and Service
源URL[http://ir.ia.ac.cn/handle/173211/11838]  
专题自动化研究所_智能感知与计算研究中心
通讯作者Lijun, Cao
作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Lijun, Cao,Xu, Zhang,Weihua, Chen,et al. License Plate Localization With Efficient Markov Chain Monte Carlo[C]. 见:. 厦门. 2014-6.

入库方式: OAI收割

来源:自动化研究所

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