UAV with Vision to Recognise Vehicle Number Plates

A team of researchers in Pakistan lead by Naveed Ali Khan Kaimkhani from the INET Technical University Berlin, Berlin, Germany has just published a study that explains how Automatic Number Plate Recognition (ANPR) is performed on real-time images using MATLAB with the help of a UAV to analyze the effect of certain factors which play a key role in identifying the vehicle license plate correctly.

The camera gimbal angle, the height of the UAV from the vehicle, and the relative speed of the UAV w.r.t vehicle are all determining factors.

The most emerging application of UAVs today is to provide security and surveillance, and they are mostly used for vehicle number identification. Typical Automatic Number Plate Recognition (ANPR) uses static high-resolution cameras mounted in specific places to identify the vehicle’s number plates. Identifying the characters on the number plate becomes a very crucial task when the number plate is at an arbitrary angle to the drone camera.

Almost all applications of UAVs require cameras either to perform specific vision tasks such as facial recognition and vehicle number plate identification or to avoid obstacles in the flight path of the UAV. The most emerging application of UAVs today is to provide security and surveillance, and they are mostly used for vehicle number identification.

Typical Automatic Number Plate Recognition (ANPR) uses static high-resolution cameras mounted in specific places to identify the vehicle’s number plates. Identifying the characters on the number plate becomes a very crucial task when the number plate is at an arbitrary angle to the drone camera. The camera gimbal angle, the height of the UAV from the vehicle, and the relative speed of the UAV w.r.t vehicle play a very key role in identifying the vehicle license plate correctly.

This study explains how Automatic Number Plate Recognition (ANPR) is performed on real-time images using MATLAB with the help of a UAV to analyze the effect of the above-mentioned key factors. The process is completed in three steps: collecting visual data from the drone, processing that data, and obtaining the recognized number plate.

Photo: Image captured using UAV

Source: Hindawi