Metropolitan cities around the world are putting effort towards a common goal of smart and sustainable urban development as smart cities initiative. To realize smart transportation systems as part of smart cities, automatic recognition of vehicle license plates is essential for border checkpoint control, traffic and red-light violation, monitoring of vehicles entering and leaving critical infrastructures and government agencies. This paper presents an implementation of automatic license plate recognition system using vehicle license plates in Myanmar as a case study. The proposed approach can be used to train for recognition of country-specific vehicle license plates. Collecting more than 1200 actual license plate images, training and evaluating the performance, our implementation achieves 90% accuracy for recognizing characters of the license plates, and 100% accuracy for detecting total number of vehicle license plates in the videos. To the best of our knowledge, we are the first in Myanmar having a dataset of actual license plate images/videos and successfully implemented such an automatic recognition system.


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    Title :

    Automatic Vehicle License Plate Recognition System for Smart Transportation


    Contributors:


    Publication date :

    2018-11-01


    Size :

    1345462 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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