As an essential task, vehicle detection aims to provide information assisting vehicle counting, vehicle speed measurement, identification of traffic accidents, traffic flow prediction, etc. There are various sensors used to collect continuously- generated traffic information.

1. SRM INSTITUTE OF SCIENCE AND TECHNOLOGY, RAMAPURAM CAMPUS
SEMINAR
Design and implementation of Vehicle Detection System
for various security purpose.
BATCH NO: 7
SAMMED S.P (RA1911003020381)
NIKHIL PRAKASH .J.S (RA1911003020391)
SHIKHA RAI (RA1911003020410)
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2. Introduction
➔ Now a days, the number of Vehicle is increasing more so for security purpose
and for Vehicle survey we are using digital systems like Automated Vehicle
recognition system, with this we can detect the Vehicle number plate.
➔ So we have to implement this digital system in CCTV of traffic signal areas to
recognize the vehicles for various security purpose.
➔ It would focus and capture various attributes of vehicles (Type of vehicle,
model of vehicle, Color, Number Plate of vehicle, accessories) captured
from various CCTV Systems through distributed intelligence (software)
along with time and location stamp over the period of various targeted
persons.
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3. Objective
➔ As an essential task, vehicle
detection aims to provide
information assisting vehicle
counting, vehicle speed
measurement, identification of
traffic accidents, traffic flow
prediction, etc. There are various
sensors used to collect
continuously-generated traffic
information.
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4. ❑ Tejendra Panchal et al [6] address License Plate limitation with the
incorporated division approach.
❑ ZEZHI CHEN. In this paper, vehicle detection is based on categorizing
vehicle such as car, bus, vans, and motorcycle and
counts them. The method proposed for research is a
new background GMM and make use of shadow
removal method .
Literature Survey
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5. The study in this paper is to analyze the
existing limitation in Video Image
Vehicle Detection System (VIVDS) for
traffic surveillance and offer new contour
of VIVDS for intersection monitoring in
urban area. The Proposed method for
vehicle detection are GMM (Gaussian
Mixture Model).
YIYAN WANG
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6. ❑ Sandipan Chowdhury et al [4] proposes calculations to confine vehicle
number plates from regular foundation pictures.
❑ Sahar S. Tabrizi et al [5] presents another technique for Iranian
License plate acknowledgment frameworks that
will expand the exactness and lessening the
expenses of the acknowledgment period of these
frameworks.
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❑ Utkarsha Gurjar et al [7] utilized for distinguishing the stolen
vehicles and is actualized at police checkpoints
and toll square.
❑ Poorya Sagharichi Ha et al [8] exhibit an Automatic License Plate
Recognition System (ALPRS) to distinguish tags
which is an utilization of picture preparing.

8. Existing System
IJMTER (International Journal of Modern Trends in Engineering and Research) has created Vehicle
Detection, Tracking and Counting Objects For Traffic Surveillance System Using Raspberry-Pi.
Linux Operating System:
Linux or GNU/Linux is a free and open-source software operating system for computers. The operating system
is a collection of the basic instructions that tell the electronic parts of the computer what to do and how to
work.
Free and open-source software (FOSS) means that everyone has the freedom to use it, see how it works, and
changes it.
Segmentation Detection Tracking Counting
Input
Frames
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9. Proposed Work
➔ The proposed system is built with Raspberry pi with pi camera (or USB camera) to capture vehicle
images on traffic scenes or remote area with OpenCV libraries.
➔ The camera is kept at a remote place to capture the moving vehicle videos and it can be controlled by
the desktop or laptop or through the android devices and can analyze the Vehicle data.
➔ To access the remote Raspberry Pi from computers or any devices, a static IP address is assigned to
Raspberry Pi and is connected to the private network, so that we can access information about the
Vehicle from any remote place.
➔ Acquiring data from traffic scene using Raspberry Pi and Pi camera (or USB camera)it consists of
images of Vehicles from different angles and non-vehicles
➔ Extracting images from video sequence and preprocess them using Grayscale filter and Medium filter
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10. Detecting Model of the vehicle
➔ In order to detect the car based on our feature set, we would need a prediction model.
➔ For this particular case we will be using Linear Support Vector Machines.
➔ It is a supervised learning model which will be able to classify whether something is a car or not after we
train it.
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11. Detecting Colour of the vehicle
➔ The Pi camera and USB Camera capture a video in a standard color format (RGB) at a given frame rate.
➔ In order to segment the vehicle colors more absolutely we convert RGB format to HSV.
➔ To segment absolute colors of vehicles HSV color space is well suited because of the wide range of
color space and can differentiate easily.
➔ After conversion, the HSV format image is split into three separate channels and is processed.
Therefore vehicle color will be separated from background color.
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12. Modules
✔ Arduino is open source physical processing which is base on a microcontroller board and an
incorporated development environment for the board to be programmed. Arduino gains a few inputs,
for example, switches or sensors and control a few multiple outputs, for example, lights, engine and
others.
✔ GPS stands for Global Positioning System and used to detect the Latitude and Longitude of any location
on the Earth, with exact Universal Time Co-ordinate time. This device receives the coordinates from the
satellite for each and every second, with time and date.
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13. 13
Existing Work Proposed work
Vehicle Detection, Tracking and
Counting Objects For Traffic
Surveillance System Using
Raspberry-Pi.
It is built with Raspberry pi with pi
camera (or USB camera) to capture
vehicle images on traffic scenes or
remote area with OpenCV libraries.
Linux or GNU/Linux is a free and
open-source software operating
system for computers.
A static IP address is assigned to
Raspberry Pi and is connected to the
private network.
Free and open-source software
(FOSS) means that everyone has the
freedom to use it, see how it works,
and changes it.
we can access information about the
Vehicle from any remote place using
Static IP.
Comparison between Existing work and Proposed Work

14. 14
Comparison Chart

15. Conclusion
The proposed Idea Vehicle recognition system will help the traffic system and Vehicle survey
system to work more efficiently without hassle.
A system with Raspberry Pi and USB camera is being used for real-time vehicle model detection,
color detection and Speed Detection.
Reduces physical space and storage space by capturing the video, only when the movement is
found.
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16. Application
➔ Vehicle counting
➔ Vehicle speed measurement
➔ Identification of traffic accidents
➔ Traffic flow prediction
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17. THANK
YOU
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