1. INSTITUTE OF ENGINEERING
THAPATHALI CAMPUS
THAPATHALI,KTM.
using
ALTR
ANPR
(Automatic Number Plate Recognition)
(automatic line tracking robot)
Group Members:-
Project Supervisor-
Raju Pandey
&
Pravin shakya
Ashok Basnet /DCT/407
Bishnu Parajulli /DCT/410
Ishwor Pd.Rijal /DCT/416
Kabindra Kaji Bajrachraya 062/DCT/419
Kiran Karki /DCT/420
Krishna Bdr Shrestha /DCT/421
Mohan Pandey /DCT/422
Ramhari Regmi /DCT/430

2. Introduction

3. Objectives
To be familiar with image processing technique for detection of Number plate area.
To be familiar with OCR.
To be familiar with MATLAB software.
To interface hardware using parallel port of the computer.
To develop a line tracking robot which can move in a guided track and detect the closed door.
To be familiar with Microcontroller and related components for building automatic robot.
To know assembly level programming language and implement it in ALR.
To develop a security system.

4. (SIMPLY INTRODUCTION)
1.MAT LAB
2. OCR (Optical Capturing Recognizer)
3. PARALLEL PORT
4. ALGORITHM:
Convert Image into Binary
Detecting Number Plate Area
5. REQUIREMENT:
Software
Hardware
6. SYSTEM BLOCK DIAGRAM:
ALR (Automatic Line –Tracking Robert)
Image Processing
Parallel Port
Data Control
7. DESIGN:
DFD (Data Flow Diagram)(0,1)
ERD (Entity Relationship Diagram)
8. AUTOMATIC LINE-TRACKING ROBORT
9. SYSTEM
10. ESTIMATED COST
11. DISCUSSION SND CONCLUSION

5. 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.

6. Requirements Software requirement Hardware requirement MATLAB R2008aPC
Automatic line tracking robot
Windows xp
Webcam Driver
Webcam

7. System Block Diagram

8. System

9. Design

10. Design 1.DATA FLOW DIAGRAM Level O DFD (context diagram) Level 1 DFD
2 ENTITY RELATIONSHIP DIAGRAM

11. Level 0 DFD

12. Level 1 DFD

14. Image Processing and Matlab

15. Matlab Matlab is an abbreviation of Matrix Laboratory.
It is a popular Mathematical Programming Environment used extensively in Education as well as in Industry.
The trick behind Matlab is that everything is represented in the form of arrays or matrices.
Mathematical Operations starting from simple algebra to complex calculus may be conveniently carried out using this environment.
The main use of Matlab in Software Development is Algorithm Design and Development.
Code developed in Matlab can be converted into C, C++ or Visual C++.
Additionally Matlab may be called as ActiveX Object from still higher level languages like Visual Basic, etc.

16. Image Processing
Image Processing generally involves extraction of useful information from an image.
This useful information may be the dimensions of an engineering component, size of diagnosed tumor, or even a 3D view of an unborn baby.
The main areas of application of Image Processing are Bio-Medical, Engineering, Quality Control, Face Detection , Traffic Control etc.

17. Image Processing (contd.)
Source Image
Formatting
Observed Image
Conditioning
Labeling
Conditioned Image
Labeled Image
Grouping
Extracting
Grouped Image
Target Image
Matching
Extracted Image
Templates
Conditioned Image

18. Image Processing in Matlab
Images can be conveniently represented as matrices in Matlab.
One can open an image as a matrix using imread command.
The matrix may simply be m x n form or it may be 3 dimensional array or it may be an indexed matrix, depending upon image type.
The image processing may be done simply by matrix calculation or matrix manipulation.
Image may be displayed with imshow command.
Changes image may then be saved with imwrite command.

19. Algorithms

20. System Algorithm Input image from webcam. Convert image into binary.
Detect number plate area.
Segmentation.
Number identification.
Save to file in given format

21. Algo: Input Image Capture image from webcam.
Store the captured image into a image file for further processing.

22. Algo: 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.

23. Algo: 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’
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.

24. Algo: Segmentation Filter the noise level present in the image.
Clip the plate area in such a way that only numbers of plate area extracted.
Separate each character from the plate.

25. Algo: Number Identification
Create the template file from the stored template images.
Resize image obtained from segmentation to the size of template.
Compare each character with the templates.
Store the best matched character.

26. Algo: Save to file in given format
Open a text file in write mode.
Store the character obtained from the number identification process to text file in given format.
Close the file.

27. Parallel Port Interfacing

28. Parallel Port
Parallel communication requires as much wires as the no. of bits in a word for its transmission.
Parallel port is generally a 25 pin female connector with which a printer is usually attached.

29. Pin Configuration of Parallel Port

30. Pin Assignment Pin No Signal name Direction Register - bit Inverted 1
nStrobe
Out
Control-0
Yes 2
Data0
In/Out
Data-0 No 3
Data1
Data-1 4
Data2
Data-2 5
Data3
Data-3 6
Data4
Data-4 7
Data5
Data-5 8
Data6
Data-6 9
Data7
Data-7 10
nAck In
Status-6 11
Busy
Status-7 12
Paper-Out
Status-5 13
Select
Status-4 14
Linefeed
Control-1 15
nError
Status-3 16
nInitialize
Control-2 17
nSelect-Printer
Control-3
18-25
Ground -

31. Interfacing System using Parallel Port
Darlington
Pair IC
(ULN2003)
Computer
Instruction
For
Door
Control
Computer
Parallel
Port
Inverting
Buffer
(CD4049)
Door
Mechanism
H- bridge
DPDT
Relay

32. Automatic Line Tracking Robot(ALR)

33. Line Tracking Robot Inverting Buffer IC (CD4049) Input from Sensor
Comparator
(LM324)
AT89s52
Micro-
controller
Motors
Relay
Darlington
Pair IC
(ULN2003)

34. Limitations

35. Limitations
Recognizes only specified font (Times New Roman) number plate only.
Can’t clearly recognize or distinguish character like B and 8, 2 and Z , 0 and O etc.
The distance of image captured is also limited.
Lighting Conditions greatly effect the image processing.

36. Cost Estimation Effort Cost= Rs.150000 Software requirements=Rs.2500
Hardware Requirements=Rs.6000
Internet Surfing= Rs.2000
Reference materials bought=Rs.5000
Transportation Cost=Rs.1000
Communication Cost=Rs.1000
Total cost = Rs. 1,67,500/-

37. ￿emonstration of ANPR usi￿

38. Conclusion and Discussion

39. THANKS To our project Supervisor Mr. Raju Pandey & Mr.Pravin Shakya
The Department of Computer and Electronics
All the Supporting Teachers in our Project