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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| 主要な著者: | , , , |
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| フォーマット: | Conference or Workshop Item |
| 出版事項: |
IEEE (IEEE Xplore)
2013
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| オンライン･アクセス: | http://psasir.upm.edu.my/id/eprint/41301/ |
| タグ: |
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| 要約: | 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. |
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