1. Vehicle Detection using
Image Processing
Made by:Ghazalpreet Kaur
Section 2(2)
B100020146
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2. Overview
First significant and crucial task is
to effectively gather information of
the surroundings.
Intrusion by a moving vehicle causes
disturbances like thermal, seismic,
acoustic, electrical, magnetic, chemical,
and optical.
Therefore, a variety of sensing
techniques have been to capture such
disruption
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3. Sensors:Sensors used for vehicle detection
and surveillance may be described
as containing three components namely :Transducers:- detect passage or presence
of a vehicle
Signal processing device:- converts the
transducer output into electrical signal
Data processing device:- consists of
computer hardware and firmware that converts
the electrical signal into traffic parameters like
vehicle presence, count, speed, etc.
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4. Deployment of sensors:Vehicle detection sensors can be
deployed in two ways:In-roadways sensors:-those
requiring installation on, embedded in, or
installation below the road surface.
Pneumatic road tube, inductive loop
detector, magnetic sensors, piezoelectric
cable, and weigh-in-motion sensors like
piezoelectric, bending plate, load cell are
such examples.
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5. Over-roadway sensors:- Those that do
not require the installation of the sensor
directly onto, into, or below the road
surface. They are mounted over the center
of the roadway or to the side of the
roadway. Video image processor,
microwave radar, active and passive
infrared, ultrasonic, and passive acoustic
array are technologies applied to overroadway sensors.
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6. Strengths and Weaknesses of
Commercially Available Sensor
Technologies
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7. Image and video processing
 The main objective of this project is
to detect the various forms of vehicle,
whether it is a jeep, sedan, a small car
or a two wheeler
 It can even detect human activity in
the region.
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8. METHODOLOGY USED
 The work has been carried out in
two domains.
 Spatial Domain– We extract the
vehicle portion from whole of the
image.
 Frequency Domain– In this we
extract the vehicle portion and take
its Fourier transform and then
analyze its spectrum.
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9. Flowchart
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10. WORKING IN SPATIAL DOMAIN
 Image acquisition
 Image absolute differencing
 Applying operations to remove noise
 Finding the boundaries of the vehicle
 Cropping the vehicle
 Calculating the aspect ratio
 Aspect ratio parameter matching with
data base for vehicle detection
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11. ASPECT RATIO
Aspect ratio is the ratio of any two
parameters
 Height to width
 Width to diagonal
 Height to diagonal
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12. Need for the aspect ratio
 Aspect ratio removes the camera
constraints, so the whole project
becomes independent of camera
position
 The aspect ratio of any vehicle
remains same irrespective of where
it is viewed from i.e. a near point or
a far point.
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13. IMAGE CORRELATION
 image correlation calculates
similarities between two images
 r = corr2(A,B) computes the
correlation coefficient between A and
B where A nd B are matrices of the
same size.
 We use image correlation in
algorithm for automatic image
acquisition and processing module.
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14. AUTOMATIC IMAGE ACQUISITION
AND PROCESSING
Capture an image and save it
as a background.
Apply the algorithm of vehicle
detection to subsequent frames
taken at a regular intervals of
time .
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15. FREQUENCY DOMAIN
 Leap frog in the module of image
processing.
 After cropping the veicle from
image ,we make a function with the
same parameters and take its
fourier transfrorm.
 Now we analyse this spectrum to
determine the type of vehicle.
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16. Importance of the project and its real
life application.
 Automated Vehicle Traffic Management in
crowded cities and on express highways
and other national highways.
 Automated vehicle toll tax collection.
 Useful from security point of view.
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17. THANK YOU
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