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...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Abdul Halin, Alfian, Mohd. Sharef, Nurfadhlina, Jantan, Azrul Hazri, Abdullah, Lili Nurliyana
التنسيق: Conference or Workshop Item
منشور في: IEEE (IEEE Xplore) 2013
الوصول للمادة أونلاين:http://psasir.upm.edu.my/id/eprint/41301/
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الوصف
الملخص: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.