ANPR(Automatic Number Plate Recognition) Using ALR(Automatic Line Tracking Robot)

It is almost known that the world is nowadays being more dependent in the computer than the human manpower. Today in the developed countries more than 90% of the job is done by automated system and this is due to the accuracy, reliability and versatile nature of the computer. In the developed western countries many big factories, nuclear plants, communication centers all of them are under the control of the computer because that’s not the place where human hand can reach up. To add the further mile for this step we have presented an automated number plate recognition using automatic line tracking robot. The 
project is based on image processing technology using popular software MATLAB. 
        The ANPR (Automatic Number Plate Recognition) using ALR (Automatic line 
Tracking Robot) is a system designed to help in recognition of number plates of vehicles. This system is designed for the purpose of the security and it is a security system. This system is based on the image processing system. This system helps in the functions like detection of the number plates of the vehicles, processing them and using processed data for further processes like storing, allowing vehicle to pass or to reject vehicle. This system also helps to conduct the graphic images of the vehicles which can be further stored in the database in text format reducing size of data to be stored.  


 INTRODUCTION 
           Massive integration of information technologies into all aspects of modern life caused demand for processing vehicles as conceptual resources in information systems. Because a standalone information system without any data has no sense, there was also a need to transform information about vehicles between the reality and information systems. This can be achieved by a human agent, or by special intelligent equipment which is be able to recognize vehicles by their number plates in a real environment and reflect it into conceptual resources. Because of this, various recognition techniques have been developed 
and number plate recognition systems are today used in various traffic and security applications, such as parking, access and border control, or tracking of stolen cars. 
           In entrance gate, number plates are used to identify the vehicles. When a vehicle enters an input gate, number plate is automatically recognized and stored in database and black-listed number is not given permission. When a vehicle later exits the place through the gate, number plate is recognized again and paired with the first-one stored in the database and it is taken a count. Automatic number plate recognition systems can be used in access control. 
For example, this technology is used in many companies to grant access only to vehicles of authorized personnel. 
           In some countries, ANPR systems installed on country borders automatically detect and monitor border crossings. Each vehicle can be registered in a central database and compared to a black list of stolen vehicles. In traffic control, vehicles can be directed to different lanes for a better congestion control in busy urban communications during the rush 
hours. 
           Automatic Line Tracking Robot (ALR) is used in this project as a vehicle which contains circuitry for moving in a guided track. It will have mechanism to detect the opened and closed door. It also will have capacity to park in the given parking area. 

Some diagrams:-> 

Project Design: 

System Block Diagram of the Project 
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       The project “ANPR based security system using ALR" was developed as III year II part project of Diploma In Computer Engineering, Thapathali Campus. The project was designed keeping in mind the automation of the number plate detection system for security reason that could replace the current system of manual entry. This project was a success in recording the number plate of a vehicle although it has got it’s own limitation of image processing and other hardware requirements. From this project we learn about image processing and OCR(Optical Character Reader),hardware interface and automatic line tracking robot(ALR). The automatic line tracking robot was developed for the 
demonstration of actual system and to have the knowledge of robots. The mechanical parts of the vehicle were designed by Robotics and Automation Club, Thapathali Campus. The basic focus of the project was in the image processing using MATLAB. The MATLAB v7.6 was used as programming tool which provides many features related to image processing. The 
parallel port interfacing was done to control the door mechanism for giving entry to the vehicle. This project implements above processes to accomplish a task of “ANPR based Security System with ALR”. Practical implementation of the project range from small use such as keeping record of incoming and outgoing vehicles from the parking area to a vast implementation such as security system. The project was completed within 6 months time period.
ALGORITHMS
System Algorithm

1. 1.Input image from webcam.
2. 2.Convert image into binary.
3. 3.Detect number plate area.
4. 4.Segmentation.
5. 5.Number identification.
6. 6.Save to file in given format

Input Image

1. 1.Capture image from webcam.
2. 2.Store the captured image into a image file for further processing.

Convert Image into Binary

1.Identify the intensity of the image.

If image intensity = high Reduce intensity Else if intensity = low Increase intensity Else No change.

2.Convert image into grayscale. 3.Calculate appropriate threshold value for the image. 4.Convert the image into binary image using the calculated threshold.

Detecting Number plate area

1.Fill small holes including numbers of Number plate so that number plate area will be large to isolate from figure. 2.Determine width and height of the image. 3.Scan each pixel of line counting number of white pixels in the following system,

If number of ‘white’ pixels < x; pixels become ‘black’ Else; no change If number of ‘white’ pixels > y; pixels become ‘black’ Else; no change The value of x and y may be changed according the image intensity and plate area.

4. Use the step no. 3 for both horizontal and vertical direction. 5.Check number of possible areas. 6. Logically AND with binary image obtained at “Convert image into binary algorithm. 7.Crop the required area.

Segmentation

1.Filter the noise level present in the image. 2.Clip the plate area in such a way that only numbers of plate area extracted. 3.Separate each character from the plate.

Number Identification

1.Create the template file from the stored template images. 2.Resize image obtained from segmentation to the size of template. 3.Compare each character with the templates. 4.Store the best matched character.

Save to file in given format

1.Open a text file in write mode. 2.Store the character obtained from the number identification process to text file in given format. 3.Close the file.

Download Report and source codes of the project here:-;

1. Report
2. Source Codes
3. Presentation File