The purpose of Vision is to introduce a proper solution for car license plate detection used for access restriction and monitoring cars accessing the parking area through the entrance ramp.. The solution is implemented using C++ and Node.js libraries and designed as a desktop application able to detect and read car license plates from still images taken by the on-location camera.Vision analyzes images and video streams to identify license plates. The output is the textual representation of any license plate characters, the car’s color, make and model.

2. Group Members

3. Amara Jamal Ibtihaj Uddin Jaweria Nadeem Khan

4. Supervisor

5. Farhan Ahmed Siddiqui

6. Overview

7. Overview
● Today, we are on the cusp of a new automation era: rapid advances in robotics, artificial
intelligence, and machine learning are enabling machines to match or outperform humans in
a range of work activities, including ones requiring cognitive capabilities.
● Computer vision is concerned with the automatic extraction, analysis and understanding of
useful information from a single image or a sequence of images.
● Computer vision is used in many different areas. One of them is image and video processing
for purposes of object detection in these images or video files
● Nowadays, very common application of object detection in images is detection of car license
plates. This brings us to our project:

8. What does Vision do?
01 Vision functions to automatically capture an image of the vehicle’s
license plate,
02 Transforms that image into alphanumeric characters using optical
character recognition
03 Saves the entries into databases and compare the plate number
acquired to one or more databases of vehicles of interest to law
enforcement and other agencies.

9. Objective

10. The purpose of Vision is to introduce a proper solution for car
license plate detection used for access restriction and
monitoring cars accessing the parking area through the
entrance ramp. The main objective of Vision is fast detection of
license plates in case of concrete image frames. This
automatic number plate recognition can be used to store the
images captured by the cameras as well as the text from the
license plate.

11. Applications

12. Target audience/Applications
Theft Control/Anti-Crime Parking tickets Highway tolling
Petrol stations Access control Airport security

13. Vision In Pakistan

14. Vision In Pakistan
The technique of using ALPR for surveillance is already proposed by Lahore
Police to help them in catching criminals.

15. Logical Structure

16. Logical structure
Our main objective is to have Accelerated Real Time Image
Processing which is a combination of both image enhancement
and image detection algorithms to help the security systems.

17. Logical Structure

18. System Overview
Our system consists of the following units:
● Camera(s)
● Illumination
● Frame grabber
● Computer
● Software
● Hardware
● Database

19. Cycle Diagram

20. Cycle diagram
Image Acquisition
Image
enhancement
Compare and save
in database
Character
Recognition
01
02
03
04

21. Problems

22. Problems
There are a number of possible difficulties that the software must be able to cope with. These
include:
● Poor file resolution, usually because the plate is too far away but sometimes resulting
from the use of a low-quality camera.
● Blurry images, particularly motion blur.
● Poor lighting and low contrast due to overexposure, reflection or shadows.
● An object obscuring (part of) the plate, quite often a tow bar, or dirt on the plate.
● Vehicle lane change in the camera's angle of view during license plate reading.
● Circumvention techniques.
● Lack of coordination between countries or states. Two cars from different countries or
states can have the same number but different design of the plate.

23. Camera Positioning, Illumination and Angles
Accuracy degrades beyond a 30-degree horizontal or vertical angle. If possible mount the
camera high enough and angled slightly downward so as to avoid direct headlight/taillight
glare.

24. Hardware Design

25. Hardware Design
1. Resolution/Frame Rate
2. Compression = 20. A lower
3. Zipstream = Off
4. Camera Capture Mode
5. Image Appearance
6. White Balance
7. Wide Dynamic Range
8. Exposure Settings
9. Image Settings
10. Day/Night
11. IR Illumination

26. Result

27. Result
As shown in the image the result is
displayed in the way where it gives all
the relevant information about the car
including its number plate , make,
model , region, etc and all this data is
saved in our database. The algorithm
for this product is designed in a way
that it is efficient enough to not only
detect the car but also give relevant
information about it so that it is easy
to keep all the record and most
importantly for the security measure.

28. Conclusion

29. Conclusion
Vision functions to automatically capture an image of the vehicle’s
license plate, transform that image into alphanumeric characters
using optical character recognition or similar software, compare the
plate number acquired to one or more databases of vehicles of
interest to law enforcement and other agencies, and to alert the
officer when a vehicle of interest has been observed.

30. Thank you!