IRJET- Border Security using Computer Vision

Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1
BORDER SECURITY USING COMPUTER VISION
Prof.A.B.Wani1,Bhagwan Pawar2, Ashish Deshpande3, Tushar Kaul4
1H.O.D. & Associate Prof., E&TC Engineering Dept, BVCOE Lavale, Pune, Maharastra, India.
2Bhagwan Pawar, E&TC Engineering Dept, BVCOE Lavale, Pune, Maharastra, India.
3Ashish Deshpande, E&TC Engineering Dept, BVCOE Lavale, Pune, Maharastra, India.
4Tushar Kaul, E&TC Engineering Dept, BVCOE Lavale, Pune, Maharastra, India.
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - The aim of this work is to design the automated
security in order to detect, track and destroy the target for
surveillance operation. The system can be operated in two
modes, in which the target can be tracked automatically by
using microcontroller based system. Onotherhand, thesystem
can also be controlled manually in which the user has right to
select the target and performsshootingif necessary. Computer
vision is closely linked with image processing, as thecomputer
must interpret what it sees , and then perform appropriate
analysis or act accordingly. The process starts by processing
the video signal on computer by using the video camera, then
the target is selected which can be tracked further by using
different image processing techniques. After selection of
target, the microcontroller unit takesthedecisiontoshootany
unauthorized person or activity within its range. The gun is
mounted on a tripod stand and its movement is controlled by
using the stepper motor. Once the target is selected it can be
tracked by moving camera and gun. The basic purpose of this
automatic gun targeting system is to secure the border using
automation and this will reduce the human efforts.
Key Words: Computer vision, target selection , target
tracking, automatic gun .
1.INTRODUCTION
Now a days security is the major issue for all over the world.
Security is major factor in order to protect vulnerable and
valuable assets such as a person, dwelling, community and
nation from any harm. The International security issues are
also very important, especially border and coast security to
any country. The mankind of national security agencies,
maritime security organization, military forces and other
forces sacrifice their lives to protect their country people.
The lives of soldier are also very precious like other lives. So
by using advance technologies, the forces can protect their
nation supremely with minimum life losses. In this modern
era, computer base security equipment’s are very popular
among forces because they are more advance and safe for
themselves. For example drone technology the “unmanned
aerial vehicle” which is controlled automatically by
computer is very popular these days. In this technology, the
target is selected and hit by using computer based
algorithms including image processing techniques. As real
time image and video processing for object detection and
tracking has many important applications in the field of
computer vision. A very highs possible to identify three key
steps in video analysis: detection of interesting moving
objects, tracking of the detected objectsfromframetoframe,
and analysis of the object tracks to recognize their behavior
and targeted object accordingly. Anotherexisting exampleof
automatically aimed weapon is the sentry gun which aims
and fires the targets which is selected by its sensorsAnother
existing application is “Air Defense Gun” which is mounted
on the device at the top of the armytank whichautomatically
tracks and shoots low flyinga Objectdetectionwitha camera
is a revolution in image processing which itself has
applications in various civilian and military fields. These
applications include air traffic control, navigation system,
error tolerant systems, judgment problems, inspection,
target analyze, command and control, sensor management
and weapon assistance.
1.1Motion detection:
Motion detection in sequel imagesisnothingbutthe
detection of the moving object in the scene. In video
supervision, motion detection refers to the capability of the
surveillance system to detect motionandcapturethe events.
Motion detection is a software-based monitoring algorithm
which will signal the surveillance camera to begin capturing
the event when it detects motions. In motion detection, a
camera fixed to its base has been placed and is set as an
observer at the outdoor for surveillance. Any kind of small
movement with a level of tolerance it picks is detected as
motion. There are typically three approaches to moving
object detection- Temporal differencing, Averaging and
Optical flow. Temporal differencing is very adaptive to
changing environments, but generally does a poor job of
extracting all relevant feature pixels. Averagingprovidesthe
most complete feature data, but is extremely sensitive to
dynamic scene changes due to lighting and extraneous
events. Optical flow algorithm can be used to detect
independently moving objects in the presence of camera
motion; however, most optical flow computation methods
are computationally complex, andcannotbeappliedto entire
frame video streams in real-time without specialized
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

hardware. The Average image subtraction method is been
utilized in this paper for motion detection.
1.2 Motion Tracking:-
The object tracking is done after object detection.
This function gives the intelligence to the camera. An enemy
entering into cameras visual range will always be followed
by the camera after detecting it. This feature iscalledmotion
tracking. This is carry out by mounting camera on motors to
ensure its movement in the direction of motion of the
intruder. The object motion tracking depends on the
efficiency of motion detection. To attain real time motion
tracking the motion should be detected with least possible
time lag.
1.3 Problem faced in Real time environments:
In video motion detection is fundamental in many
autonomous video surveillance strategies. However, in
outdoor site where inconsistent lighting and unimportant,
but distracting, background movement is present, it is a
challenging problem. In present real time environment
where scene is not under control situation is much worse
and noisy. Due to environmental changes light may change
anytime which cause system output less meaningful to deal
with. Late has produced several background modeling
techniques,on basis of image differencing, that exhibit real-
time performance and high accuracy for certain classes of
scene.Where the environmental changes introduces
unpredictable variations in both lighting and background
movement.
2. OVERVIEW OF SYSTEM IMPLEMENTATION
In this system has various functional blocks with each
block having its specific function. Above shown all these
blocks together help the system to operate. We have a
Camera, a computer, a motor and a controller in the
system.(Fig.1) shows the system overview.
To apply the image processing we have used a simple
algorithm which is efficient for the specific system
conditions.
The conditions required for this algorithm are
(1) Presence of a single object
(2) Large contrast between object and the surroundings.
(3)Background should be plane and constant (no moving
components other than object).
When these three conditions are satisfied then our
algorithm is efficient and easy to implement. The algorithm
is presented in the flowchart as below:-
We capture the image with the help of camera and then
these visual inputs are sent to computer for processing. The
software MATLAB is used for image processing.
The inputs from camera are continuous. At the start a
particular time interval is defined for generating frames
called as frame interval. So, instead of processing the visual
inputs continuously we process these frames. The frame is
nothing but an image. This image which consists of pixels is
divided into two parts. Averaging is performed on both the
parts and then the difference of these two averages is
computed. This difference is scaled down by using a scaling
factor which depends on the conditions in which system is
operating. The movement of the gun is proportional to the
value of this difference. A threshold value is determined
depending on the operating conditions of the system.
Thus we get three conditions:-
If difference> + threshold……….gun rotates anticlockwise
If difference < - threshold………gun rotates clockwise
If - threshold < difference < + threshold …..do not rotate
3. SYSTEM FLOW AND WORKING:

The software execution is done on the images of resolution
160x120. The capture image is divided into two parts of
resolution 80x120 each. The sum of intensities of all the
pixels in a particular part is called average of that part.
Thresholding is simplest method of image segmentation,
user can choose a threshold value known as manual
thresholding or the thresholding algorithm can compute an
value automatically known as automatic thresholding.
CASE 1: when the threshold condition is - threshold< diff <
+ threshold, it indicate presence of object at median. Then
controller takes an action " don't rotate the gun".
CASE2:-When the threshold condition is diff> + threshold, it
indicate presence of object at right. Then controllertakesan
action "rotate gun anticlockwise" .
CASE 3:- When the threshold condition is diff< - threshold, it
indicate presence of object at left. Then controller takes an
action "rotate gun clockwise".
.
4. CONCLUSION
In this paper, a new method is purposed to detect motion
using the subtraction algorithm. Project proposes the
sampling by calculating the intersection of number of
background subtracted frames which are sampled over a
period of time .A video monitoring & detection system was
thus developed successfully. The systemmainlyprovides an
efficient method for surveillance purpose and aimed to be
highly beneficial for military.
REFERENCES
1] Deqing Xue, “Assessmentand analysisofthereliabilityofa
new anti-aircraft gun system”. 15-18 June 2012,
[2] Bo Bi,“Research of Anti-aircraft gun weapon system
simulation platformbasedHLAandVirtools”9-11Sept.2011,
[3]David A Mindell, “Automatic visual tracking and fire
control system for anti-aircraft machine gun”. 22nd January
2009
[4] Stuart Bennett,“Anti -Aircraft Fire Control and the
development of Integrated Systems at S Derrv. 1925-1940
[5]John Testuro Sumida, In Defence of Naval Supremacy:
Finance, Technology,and British Naval Policy 1889-1914,
London:Routledge 1989.

IRJET- Border Security using Computer Vision

Recommended

More Related Content

What's hot (18)

Similar to IRJET- Border Security using Computer Vision (20)

More from IRJET Journal (20)

Recently uploaded (20)

IRJET- Border Security using Computer Vision