Determine The License Plate of the Vehicle in Violation of a Specific Speed

Hanan Aqeel musaeid; Kadhim Mahdi Hashim2

doi:10.32792/jeps.v12i2.170

المؤلفون

Hanan Aqeel musaeid
Kadhim Mahdi Hashim2

DOI:

https://doi.org/10.32792/jeps.v12i2.170

الكلمات المفتاحية:

ACF، Euclidean distance، fps.

الملخص

The problem of detecting cars that violate the speed limits set by a certain country or region is a matter
that needs to find an effective way to solve it in order to help the traffic police in this matter, which is
very important, Automatic License Plate Detection (ALPD) is a critical technology for effective traffic
management. It is utilized in a variety of applications including. toll payment systems, parking, and traffic
control, a convolutional neural network (CNN)-based technique for high-accuracy real-time car license
plate detection is presented in this paper. Many modern approaches for detecting car license plates are
used under specified conditions or with significant assumptions. When the car license plate is assessed
photographs as a result of manual capture by traffic cops or camera deviation, there is a degree of
rotation, they perform poorly. Thus, a new framework for multi-directional car plate detection according
to a Region-based Convolutional Network method (R-CNN) that is faster. A number tests have shown
that the suggested method surpasses in terms of accuracy and computing cost, existing state-of-the-art
approaches. The accuracy rate in detecting vehicle license plates reached 98%.

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