# Matlab Code For Car Number Plate Recognition System

by admin in on July 19, 2020

### Project Description

Number Plate Recognition system is a technology for automatically reading vehicle number plates. It 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 controlling traffic over the roads, Petrol Pumps, Shopping Malls, Airports, highways, toll booths, Hotels, Hospitals, Parking lots, Defense Military checkpoints, etc. We took an approach for the recognition of number plate using MATLAB Image Processing. Many times images are noisy, different countries have different patterns for license plates. This makes the task very difficult. So it becomes very important to select the proper algorithm for this purpose.

### Dataset Description

In the dataset, we have included license plates of cars from different countries. The number plate should
be dominant in the image. They also differ in the number of digits, the color of the license plate, size of the image.
We have taken a few pictures as our primary dataset. The pictures were taken from the internet. As license plate can be both on the front part or rear part of the car so we attempt to test both. The first two pictures are the front view of the car and the second two pictures are the rear view of the car. We take both types of pictures to see if our algorithm works correctly for both of them or not.

### Methodology

We have developed our own algorithm with the help of the Matlab website (Mathworks) and analyzing different built-in functions of Matlab. There are three main steps :
1. localization of the plate
2. segmentation of the characters
3. detection

#### Flowchart

In the following flowchart, we tried to show the steps of how the code is working:

#### Function Used

1. imread() This command is used to open the image into the MATLAB from the target folder.
2. rgb2gray() This command is used to convert the RGB image into a grayscale format.
3. imbinarize() This command is used to Binarize 2-D grayscale image or simply we can say it converts the image into the black and white format.
4. edge() This command is used to detect the edges in the image, by using various methods like Roberts, Sobel, Prewitt, and many others.
regionprops() This command is used to measure the properties of the image region.
5. numel() This command is used to calculate the number of array elements.
6. imcrop() This command is used to crop the image in the entered size.
7. bwareaopen() This command is used to remove small objects from the binary images.

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#### Release Information

• Price
:

\$11.99

• Released
:

July 19, 2020

• Last Updated
:

July 19, 2020