License Plate Localization using a Naive Bayes Classifier

被引：0

作者：

Halin, Alfian Abdul ^{[1
]}

Sharef, Nurfadhlina Mohd. ^{[1
]}

Jantan, Azrul Hazri ^{[1
]}

Abdullah, Lili Nurliyana ^{[1
]}

机构：

[1] 43400 Univ Putra Malaysia, Fac Comp Sci & Informat Technol, Serdang, Selangor, Malaysia

来源：

2013 IEEE INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING APPLICATIONS (IEEE ICSIPA 2013) | 2013年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a probabilistic technique to localize license plates regions for cars adhering to the standard set by the Malaysian Road Transport Department. Images of the front/rear-view of cars displaying their license plates are firstly preprocessed, followed by features extraction generated from connected components analysis. These features are then used to train a Naive Bayes classifier for the final task of license plates localization. Experimental results conducted on 144 images have shown that considering two candidates with the highest posterior probabilities better guarantees license plates regions are properly localized, with a recall of 0.98.

引用

页码：20 / 24

页数：5

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