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License Plate Localization With Efficient Markov Chain Monte Carlo
Lijun, Cao; Xu, Zhang; Weihua, Chen; Kaiqi, Huang
2014-06
会议名称International Conference on Internet Multimedia Computing and Service
会议录名称Proceeding of International Conference on Internet Multimedia Computing and Service
会议日期2014-6
会议地点厦门
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.
关键词License Plate Localization Feature Likelihood Mcmc Proposal Probability
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/11838
专题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],2014.
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