Automated Number Plate Recognition

      This blog shall look into and also take you through the process of understanding and building a ANPR system. An ANPR - Automated Number Plate Recognition system is s a technology that uses optical character recognition on images to read vehicle registration plates. It can use existing closed-circuit television, road-rule enforcement cameras, or cameras specifically designed for the task. ANPR is used by police forces around the world for law enforcement purposes, including to check if a vehicle is registered or licensed. It is also used for electronic toll collection on pay-per-use roads and as a method of cataloging the movements of traffic for example by highways agencies.

          There are multiple phases in ANPR system

Stages of Automates Number Plate recognition 

          The image can be captured any ordinary camera, or special LPR- license plate recognition cameras can be used to get a better performance and accuracy from the system. LPR camera are  built with special hardware and software technologies which helps to identify number plates of vehicles with:

      1) High speed

      2) Headlight glare

      3) Ability to capture images at high frames per second

      4) High resolution 

LPR vs Regular cameras 

          The typical set up is where the camera is mounted on a system or a cell or a pole and captures the images of vehicles that pass by. In the case of traffic cameras the cameras are mounted on poles and it captures picture of vehicles are break the law. In the case of a parking system the camera is mounted on the cell which captures the pictures and grants permission for the vehicle and also prints a ticket. In both the approaches the cameras are made to focus on the vehicle and capture an image of the vehicle. Second phase is the prepossessing phase, where the image is converted form an RGB to a binary image and any noise present are removed.

Camera mounted on a cell pod

          The third phase involves detecting the location of the number plate. This process can be made simple based on the application / implementation of the system. For a ANPR system at a parking lot the camera is static and mounted at a location, hence this task of detection the number plate can be simplified into detecting the expected region where the number plate may lie (this may be specific to countries).

Once we identify and extract the location of the number plate we can run the fourth phase to extract the characters form the number plate.

          The fourth phase involves extracting the character from the number plate. Each connected component is identified and matched to the templates. A round of dilation and erosion is run to clearly identify each character in the number plate. A characters/ the connected components identified are correlated to the templates to identify the characters and print the output.

         

In this blog we shall look into building an ANPR system designed to detect number plates of Indian vehicles. We build a system that can be directly implemented in a real world situation. The setup is simple, the image can be obtained by any camera mounted to a system. We have used a 5 MP camera from an Iphone to collect our data set. The camera is mounted in a fashion that the vehicle fits in the frame of the image captured. We then feed this image to the Matlab code which segments out the number plate region from the number plate, then identifies the characters and then prints the output.

Abhilash K R

Shashidhar Pai

Dedeep Reddy S