Presently in nowadays an allowance of development on vehicle activity is observed. For the reason that is the manual checking and traffic management turns into a noteworthy issue. The fast increment in human populace had likewise requested an expansion in vehicles so the toll accumulation and tag acknowledgment for police is additionally troublesome. There be presents a result many different techniques on traffic management and surveillance are employed to reduce the complexities of the traffic man-agement. This proposed work is mainly used to outline and create in another proficient automated toll framework will be a decent minimal effort elective among the current frameworks. In this presented work a survey on automatic number plate recognition technique is presented. Additionally different methods and techniques are defined that helps to provide accurate estimation of the vehicles number plate recognition (VNPR). In addition of that a model for accurate NBR is also incorporated in this work, which is implemented in near future and their performance is eval-uated. The proposed work is established on computer vision vehicle detection using Open CV Python in Embedded Linux platform. The work is designed by using Intel/AMD processor. In this camera catches picture of vehicles going through toll corner along these lines a vehicle recognized through camera. Depending on the tag of vehicle, grouping of light weight and overwhelming weight vehicles is fin-ished. Further information is handed to DBMS, it is having web server set up on it and also it shows the information approximately the vehicle.
Survey on Efficient Automated Toll System for License Plate Recognition Using Open CV
01.07.2018
650427 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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