This document presents a seminar on a vehicle number plate recognition system by Prashant Dahake. The system uses image processing techniques to identify vehicles from their number plates in order to increase security and reduce crime. It works by capturing an image of a vehicle, extracting the license plate, recognizing the numbers on the plate, and identifying the vehicle from a database stored on a PC. The system utilizes a series of image processing technologies including OCR to recognize plates more accurately than previous neural network-based methods. It was implemented in Matlab and tested on real images.

1. A
Seminar on
Vehicle Number Plate Recognition
System
Presented by
Prashant Dahake
Mtech (CSE)
Dept. of Computer Science & Engineering
2013-2014
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2. Introduction
 security is big issue, In highly restricted areas. As well as in public places.
 VNPR system is image processing technology. which uses number plate
to identify the vehicle.
 earlier method is based on neural n/w, that requires highly trained data.
 presents system makes use of an OCR technique.

3. Aim
 To Reduce Crime and the Fear of Crime.
 Reduce Burglaries
 Reduce Vehicle Crime.
 Reduce shop theft , Reduce damage .
 Reduce motorcycle / traffic related nuisance

4. System model
 hardware model
 software model

5. Software Model consist of series of image processing
technology
 Capture image
 Extract the plate
 Extract the plate from the image.
 Recognize the numbers from the extracted plate.

6. Hardware model consist of
 sensors to sense the presence of a vehicle.
 camera to capture the image, a motor with motor driver circuit to
control to barrier
 microcontroller for controlling the complete hardware
 PC on which algorithm is executed.

7. Block diagram of working system

8. Conclusion and future scope
 The automatic vehicle identification system plays an important role
in detecting security threat.
The system use series of image processing techniques for
identifying the vehicle from the database stored in the PC
 The system is implemented in Matlab and it performance is
tested on real images.
 The system robustness and speed can be increase if high
resolution camera is used.

9. REFERENCES
1. Muhammad Tahir Qadri, Muhammad Asif’, “automatic number plate
recognition system for vehical identification using optical character
recognition”, 2009 International Conference on Education Technology
and Computer .
2. D.Renuka devi, D .KanagapushpavaUi, “Automatic License Plate
Recognition”, 2011 IEEE.
3. V. Kasmat, and S. Ganesan, “An efficient implementation of the Hough
transform for detecting vehicle license plates using DSP’s,” IEEE
International Conference on Real-Time Technology and Application
Symposium, Chicago, USA, pp. 58-59, 2005.
4. Kumar Parasuraman, Member, IEEE and P.Vasantha Kumar, "An
Efficient Method for Indian Vehicle License Plate Extraction and Character
Segmentation", 2010 IEEE International Conference on Computational
Intelligence and Computing Research.