Here is the presentation of Traffic Sign identification and recognition using some network fundamentals. This method of traffic sign recognition is the most efficient way to detect traffic sign through GPS location.It is very easy to implement.

1. At
GTU PG School , BISAG Campus, Gandhinagar
CDAC-GTU-BISAG ME Program
IEEETopicPresentation
1
PRESENTATION ON
By : KISHAN PATEL
M.E ITSNS
14th October 2016

2. CONTENTS
 Introduction
 Challenges to overcome
 Solution
 Conclusion
 References
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3. INTRODUCTION
 Traffic Sign Localization and recognition system
using Network fundamentals e.g. (Client and
Server)
 Identification and recognition of Traffic Signs
(TSs) is an area of great interest in “Intelligent
Transportation Systems”
 Over the last decade, numerous camera-based
platforms have been developed to detect and
recognize traffic signs. 3

4. CHALLENGES
 Non-appearance of signs
as a result of unpleasant
weather conditions, as
shown in Figure
 The detection of TSs in
nighttime conditions
imposes additional
challenges that render
detection and
recognition more difficult. 4

5. CHALLENGES
 To overcome these problems, several solutions and
architectures have been developed.
 All these architectures are based on the detection
of TSs using cameras and image processing
techniques which might fail in detecting signs as
shown in Figure
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6. SOLUTION
 We achieve this goal by adopting a Client-Server
architecture instead of using cameras.
 Clients, represented by vehicles in our
architecture, contain GPS devices that are used to
determine their geographic position in the map.
 Server is a powerful computer dedicated to store
important information related to all traffic signs
within a given city, and to manage requests from/to
vehicles. 6

7. HOW IT’S WORKS?
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 Client(vehicle) send
request to server
 Request contains
Geographical position of
client e.g. Longitude &
Latitude

8. HOW IT’S WORKS?
 Server keep all the traffic sign information in city
including:
 Traffic sign Position (Longitude & Latitude)
 Street name
 Brief description of the content of traffic sign (e.g. speed
limit 60 km/h)
 This system’s only drawback is that the database should
be updated frequently.
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9. WHICH INFORMATION SHOULD BE STORE IN DB?
1. Traffic Sign Information
 TsContent: This field contains information carried out by TSs such
as, YIELD, STOP, Speed Limit information, etc.
 StreetName1: It represents the name of the street where the sign
is mounted.
 StreetName2: It represents the name of the second street if the
TS is located at an intersection of two named roads.
 isAtIntersection: This Boolean field indicates the value TRUE if
the TS is located at an intersection of two named roads.
 isOneWay: If this Boolean value is TRUE, both TSs situated on
the right and left of the current lane are taken into consideration
by the travelling vehicle.
 Longitude: This value represents the longitude of the traffic sign,
 Latitude: This information indicates the latitude of the traffic sign.
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10. WHICH INFORMATION SHOULD BE STORE IN DB?
2. Car Information
 StreetName1: This field represents the name of the street
where the car is travelling;
 isOneWay: If this boolean value is TRUE, both TSs situated
on the right and left of the current lane are taken into
consideration by the travelling vehicle.
 Longitude: This value represents the longitude position of the
car.
 Latitude: This value indicates the latitude position of the ca
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11. PROBLEM ARRIVES AT COMMUNICATION..
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12. FILTERING ALGORITHM
1. Load longitude and latitude values of the Vehicle and the TS
Calculate the Distance between Vehicle and TSs
if Distance ≤ threshold then
push TS information into signQueues.
else
Increase the threshold
Goto: 1
end if
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13. FILTERING ALGORITHM
2. Load full TS information of the selected sign
if Sign.StreetName1 = Car.StreetName1 then
Take the sign as result.
else
if Sign.isAtIntersection!=TRUE then
Pop this TS from sign vector
Goto: 2
else
update Vehicle information until next time instance
end if
end if 13

14. FILTERING ALGORITHM
if Car.StreetName1==Sign.StreetName2 then
Take the sign as result.
else
Pop this TS from sign vector and
Goto: 2
end if
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15. EXPERIMENT AND RESULT ANALYSIS
 We constructed a local dataset related to down-
town Ottawa, which contains all information of
traffic signs.
 We drive our car along a given street (for instance
LAURIER Street).
 This system calculates the distance between the
vehicle and appearing signs every 30 ms.
 When the distance between the vehicle and signs is
smaller than a threshold, a warning message is
then sent to the driver. 15

16. EXPERIMENT AND RESULT ANALYSIS
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17. EXPERIMENT AND RESULT ANALYSIS
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18. COMPARISON WITH VISION-BASED METHODS
 Histogram of Oriented
Gradients (HOG)
 Maximally Stable Extremal
Regions (MSER)
 Here the result can be
seen clearly that this
system is more faster then
above two method.
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19. CONCLUSION
 Traffic signs that fulfill the requirement of vehicles
are selected and communicated to drivers using
this method.
 We have compared this architecture to two vision-
based systems, and found that our system
performs better than them.
 This architecture is easy to impalement as
compare to another.
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20. REFERENCES OF IEEE PAPER
[1] Abdelhamid Mammeri, Azzedine Boukerche and Jingwen Feng
“Traffic Signs Localization and Recognition Using A qClient-Server
Architecture” Wireless Communications and Networking Conference
(WCNC), 2016 IEEE
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Abdelhamid Mammeri Jingwen Feng Azzedine Boukerche

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