IRJET- Traffic Sign Board Detection and Voice Alert System Along with Speed Control

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 05 Issue: 03 | Mar-2018 www.irjet.net p-ISSN: 2395-0072
© 2018, IRJET | Impact Factor value: 6.171 | ISO 9001:2008 Certified Journal | Page 1221
Traffic Sign Board Detection and Voice Alert System Along with
Speed Control
Anju Manjooran1, Annmariya Seby2, Anphy Varghese3, Krishnadas J4
1,2,3 Student, Department of Computer Science and Engineering, Sahrdaya College of
Engineering and Technology, Kerala, India.
4Associate Professor, Department of Computer Science and Engineering, Sahrdaya College of
Engineering and Technology, Kerala, India.
---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - Road traffic constitutes a major part in the
problem of society. As the road traffic is increasing day by day
there is a necessity of following the traffic rules with proper
discipline. Traffic rules consist of traffic sign boardsandtraffic
signals which are meant to be followed by everyone in the
society. To provide a comprehensive assistance to the driver
for following the traffic signs, Traffic SignBoardDetectionand
Voice Alert System along with Speed Control. The signboards
are captured using camera installed in the vehicle. The
captured image will undergo for image processing by SURF
algorithm in MATLAB and identify the signboard. This gives
the driver a sort of assistance which alerts the driver and
reduces the work of the driver. The main goals of this project
are detection, and recognition and gives voice alert to the
driver. Speed will be controlled automatically accordingtothe
signboard.
Key Words: Traffic Sign Board, Image processing, SURF
Algorithm, MATLAB, Voice Alert
1. INTRODUCTION
Millions of people are injured annually in vehicle accidents.
Most of the traffic accidents are the result of carelessness,
ignorance of the rulesand neglecting traffic signboards,both
at the individual level by the drivers and the society at large.
The magnitude of road accidentsin India is alarming. This is
evident from the fact that every hour there are about 56
accidents taking place similarly, every hour more than 14
deaths occur due to road accidents. When someone neglects
to obey traffic signs, they are putting themselves at risk as
well as other drivers, their passengers and pedestrians. All
the signs and signals help keep order in traffic and they also
are designed to reduce the number and severity of traffic
accidents. Some drivers believe that some traffic signs are
simply not necessary.
All road signs are placed in specific areas to ensure
the safety of all drivers. These markers let driversknowhow
fast to drive. They help to create order on the roadways and
are employed to provide essential information to drivers.
Traffic signs include many useful environmentalinformation
which can help drivers learn about the change of the road
ahead and the driving requirements. Signs which are taken
out of specific places or not visible as a result of wear and
tear can pose undesirable risks to drivers. They also tell
driverswhen and where to turn or not to turn. Inorder to be
a terrific driver, you need to have an understanding of what
the sign mean. Road signs are designed to make sure that
every driver is kept safe.
Our system will able to detect, recognize and infer
the road traffic signs would be a prodigious help to the
driver. The objective of an automatic road signs recognition
system is to detect and classify one or more road signs from
within live colour images captured by a camera.
In this base paper we provide alertnesstothedriver
about the presence of traffic signboard at a particular
distance apart. The system providesthedriverwithrealtime
information from road signs, which consist the most
important and challenging tasks. Next generate an acoustic
warning to the driver in advance of anydanger. Thiswarning
then allows the driver to take appropriate corrective
decisions in order to mitigate or completely avoid theevent..
However, sometimes, due to the change of weather
conditions or viewing angles, traffic signs are difficult to be
seen until it is too late. First, it is necessary to select the
hardware equipment to solve this problem.Thesecondstage
is based on colour processing, or object detection method
based on rapid colour changes. Image processingtechnology
is mostly used for the identification of the signboards. The
alertness to the driver is given as audio output. If the driver
is not following the alert the automatic braking system get
activated and the speed of the vehicle get regulatedbasedon
the signboard.
2. EXISTING SYSTEMS
Road traffic constitutes a major part in the problem of
society. Some existing methods deals with the automatic
detection and recognition of traffic sign is a challenging
problem, with a number of important application areas,
including advanced driver assistance systems, road
surveying, and autonomous vehicles. While much research
exit on both the automatic detection and recognition of
symbol-based traffic sign, and the recognition of text in real
scenes there are far less research focused specifically on the
recognition of text on traffic information signs. Thiscouldbe
partly due to the difficulty of the task caused by problem,
such a illumination and shadow, blurring, and sign
deterioration. There are projects on traffic sign detection
and alert .That project mainly worksas a mobile application.

Speed control system is not implemented in the existing
systems along sign detection.
Driver gets advance information about the
upcoming hurdle. Also the costly and not practically to place
transmitter in each and every signboard. Only after login to
the application then getting the alerts. LCD is used only for
testing purpose. Bluetooth to transfer data to the android
mobile. For the demo concern, android mobile is used to
display images. As a future product, the embedded unit and
android application will be integrated in a single unit.
Accuracy high and the suffersfrom poor weatherconditions.
The complete set of road traffic signs used in our training
data and recognized by the system .Candidates for traffic
symbols are detected as MSERs. The MSERs are regions that
maintain their shape at several levels when the image is
thresholder. Detection method was selected due to its
robustness to variations in contrast and lighting conditions.
The detecting candidatesfor road signs bybordercolour,the
algorithm detects candidates based on the background
colour of the road sign because they persist withintheMSER
process.
3. PROPOSED SYSTEM
3.1 Overview of the System
Very often we see that many road accidents take place. This
can be due to driver’s ignorance of traffic signals and road
signs. As the road traffic is increasing day by day there is a
necessity of following the traffic ruleswithproperdiscipline.
Traffic signboard detection is an important part of driver
assistant systems. The basic idea of proposed system is to
provide alertness to the driver about the presence of traffic
signboard at a particular distance apart.
The project can be entirely divided in to two
sections
1. Sign Detection and Alert
2. Speed Control
The system provides the driver with real time information
from road signs, which consist the most important and
challenging tasks. It generates an acoustic warning to the
driver in advance of any danger. This warning allows the
driver to take appropriate actions in order to avoid the
accident. Image processing technology is mostlyusedforthe
identification of the signboards. The alertnesstothedriveris
given as an audio output. Automatic braking system gets
activated and the speed of the vehicle gets regulated based
on the signboard.
Figure 1: Flow chart of the System
3.2 Working of the System
The camera is placed at the front of the vehicle will
capture the image of the traffic sign board .Then the data is
send to the MATLAB program in the system where it is
compared and recognize the traffic sign from the database
using the SURF algorithm. It also provide voice alert to the
driver using the tts command through the speaker .After
identifying the traffic sign there will be corresponding
display of the command through the LCD. When the system
identified traffic sign boards of speed limit, stop, turning,
hump and such speed reducing signboards the speed of the
vehicle is reduced to certain range gradually if the speed of
the vehicle is above the limit. At this time if the drivertriesto
accelerate the speed of the vehicle above the limit it cannot
be done for certain range of the time.

Figure 2: Block Diagram of the System
3.3 Surf Algorithm
The SURF (Speed Up Robust Feature) algorithm is in itself
based on two consecutive steps (i) feature detection (ii)
description.
The main steps coming under this algorithm are:
i. Multiscale Analysis
ii. Feature Detection
iii. Feature Description
iv. Feature Matching
SURF multiscale representation based on box filters.
Comparison with linear scale space analysis. Interest point
detection. Invariant descriptorconstructionandcomparison.
Experimental validation and comparison with other
approaches.
4. RESULT AND DISCUSSION
The proposed system can operate at a range of vehicle
speeds and was tested under a various conditions. Also our
proposed system will save the valuable life by preventing
accidentsdue to the negligence of traffic signs. The projectis
mainly focus on majority of the society who used to travel
especially the night travelers and it also helps traffic police
to reduce the traffic issues. The main idea for this project is
from the road accidents that take place due to driver’s
ignorance of traffic signs. People die in these road accidents
which is a great loss for the family. It provides maximum
efficiency and is user friendly.
Chart 1: Speed V/S Time analysis at High Speed
The speed of the vehicle is reducing gradually by
this way we reduce the accident. If the vehicleisreducingthe
speed suddenly there is chance for accident by collision of
vehicle that are coming back. We also think for this situation
too. Sometimeswhile travelling at night time thedriver may
not able to see the hump in front, so by this system we can
reduce the speed of the vehicle if the driver is not aware of
the hump also.
5. CONCLUSION
This system is used to save the valuable life by preventing
accidents due to the negligence of traffic signs boards. The
project is mainly focuson majority of thesocietywhousedto
travel especially the night travelers and it also helps traffic
police to reduce the traffic issues. The main idea for this
project is from the road accidents that take place due to
driver’s ignorance of traffic signs. People die in these road
accidents which is a great loss for the family. It provides
maximum efficiency and is user friendly. At present 40%
percentage of death that taking place in a day is mainly due
to the road accidents. By our project we expected that we
can able to reduce it up to 20%.
REFERENCES
[1] Sanchita Bilgaiyan, Sherin James, Sneha. S Bhonsle,
Shruti Shahdeo, Keshavamurthy “Android Based
Signboard Detection using Image and Voice Alert
System” IEEE International Conference On Recent
Trends In Electronics Information Communication
Technology, May 20-21, 2016, India.
[2] S. Escalera et al., “Traffic-Sign Recognition Systems”,
Springer Briefs in Computer Science,2011.

[3] Jack Greenhalgh and Majid Mirmehdi, “Real-Time
Detection and Recognition of Road Traffic Signs” IEEE
Transactions On Intelligent TransportationSystems,Vol.
13, No. 4, December 2012.
[4] Frank Lindner, Ulrich Kressel, and Stephan Kaelberer
“Real-time Vision For Intelligent Vehicles” IEEE
Instrumentation & Measurement Magazine June 2001.
[5] Ian Fletcher ,Bill J.B. Arden, Chris s. cox “Automatic
Braking System Control” IEEEInternational.Symposium
on Intelligent Control Houston, Texas October 5.8 2003
[6] Chia-Hsiung Chen, Marcus Chen, and Tianshi Gao
“Detection and Recognition of Alert Traffic Signs”
[7] Rubel Biswas, Hasan Fleyeh,Moin Mostakim “Detection
And Classification Of Speed Limit Traffic Signs” IEEE
2014
[8] B. Hoferlin and K. Zimmermann, "Towards reliable
traffic sign recognition," in 2009 IV symposium, 2009,
pp. 324-329
[9] Aparna A. Dalve, Sankirti S. Shiravale, “ RealTimeTraffic
Signboard Detection and Recognition from Street Level
Imagery for Smart Vehicle” International Journal of
Computer Applications (0975 – 8887) Volume 135 –
No.1, February 2016.
[10] Jack Green Halgh and Majid Mirmehdi, senior member,
IEEE, “Real-time detection and recognition of road
traffic signs” transactions on intelligent transportation
systems, vol. 13
[11] Jack Green Halgh and Majid Mirmehdi, senior member,
IEEE, “Real-time detection and recognition of road
traffic signs” transactions on intelligent transportation
systems, vol. 13
[12] Kassem, N. Microsoft Corp., Redmond, WA, USA Kosba,
A.E.; Youssef, M.;VRF-Based VehicleDetectionandSpeed
Estimation vehicular Technology Conference (VTC
Spring), IEEE (2012)
[13] Edouard Oyallon, Julien Rabin,IPOL, “An Analysis of the
SURF Method” 5 (2015), pp. 176–
218.http://dx.doi.org/10.5201/ipol.2015.69
BIOGRAPHIES
Anju Manjooran pursuing her
B.Tech in Computer Science and
Engineering at Sahrdaya College Of
Engineering and Technology,
Thrissur, Kerala.
Annmariya Seby pursuing her
Thrissur, Kerala.
Anphy Varghese pursuing her
Thrissur, Kerala.
Krishnadas J is an Assistant
Professor in Sahrdaya College of
Engineering & Technology. He done
his specialization in Networking.

IRJET- Traffic Sign Board Detection and Voice Alert System Along with Speed Control

More Related Content

What's hot (20)

Similar to IRJET- Traffic Sign Board Detection and Voice Alert System Along with Speed Control (20)

More from IRJET Journal (20)

Recently uploaded (20)

IRJET- Traffic Sign Board Detection and Voice Alert System Along with Speed Control