License plate localization using a Naive Bayes classifier

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...

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書目詳細資料
Main Authors: Abdul Halin, Alfian, Mohd. Sharef, Nurfadhlina, Jantan, Azrul Hazri, Abdullah, Lili Nurliyana
格式: Conference or Workshop Item
出版: IEEE (IEEE Xplore) 2013
在線閱讀:http://psasir.upm.edu.my/id/eprint/41301/
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總結: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 Naïve 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.