License Plate Localization With Efficient Markov Chain Monte Carlo

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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
第一作者单位	中国科学院自动化研究所
通讯作者单位	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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License Plate Locali（389KB）	会议论文		开放获取	CC BY-NC-SA	浏览下载