International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 04 Issue: 04 | Apr -2017
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p-ISSN: 2395-0072
A Survey on Road sign Detection and ClassificationMiss. Priyanka A. Nikam1, Prof.Nitin B. Dhaigude 2 1Student, 2 Assistant
Dept. of Electronics &Telecommunication, SVPM’s COE Malegaon (Bk), Maharashtra, India
Professor, Dept. of Electronics &Telecommunication, SVPM’s COE Malegaon (Bk), Maharashtra, India
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Abstract—Traffic sign recognition plays very important role
There are many methods for solving these tasks. Road sign
in driver assistant system to disburden driver as well as in
detection is a technique due to which vehicle is able to
intelligent autonomous vehicles. This framework includes two
recognize the different signs put on the road. Traffic signs are
parts: traffic sign detection and classification of detected
used to regulate traffic. Traffic signs are used to provide
traffic signs. This paper recommends different methods for
guidance to driver. Automatic traffic sign recognition is
detection and recognition of traffic signs. Different methods
essential task of traffic regulation and guiding and warning
are used for traffic sign detection and recognition like color
driver.
segmentation, RGB to HSI model. Recognition includes HOG
Generally traffic sign provide the driver very essential
feature, shape context etc.
information for safe and efficient navigation.
Keywords— RGB model, HSI model, Hough circle transform, shape context, HOG features..
2. REVIEW OF LITERATURE 2.1 J. Stallkamp, M. Schlipsing, J. Salmen, and C. Igel, “The
1. INTRODUCTION
German traffic sign recognition benchmark: a multi-class
Traffic sign recognition has high industrial potential in
classification competition,” in Proc. IEEE IJCNN, 2011, pp.
intelligent autonomous vehicle and driver assistance
1453–1460.
system.improvement in traffic quality and safety cannot be achieved without correctly applying and maintaining road
This paper proposes the design and analysis of the
traffic signs, traffic signals and road markings. The traffic
“German Traffic Sign Recognition Benchmark” dataset and
indication sign recognition is essential to the ITS (Intelligent
competition. The results of the competition show that state-
Transport System). Every year 1.3 million people worldwide
of-the-art machine learning algorithms perform very good in
are killed on roads, and between 20 and 40 million are
the challenging task of traffic sign recognition. The
injured. A good solution to this problem would be to develop
participants achieved a very high performance of up to
system, which take into account the environment. That is why
98.98% correct recognition rate which is similar to human
today, driving safety is becoming a popular topic in many
performance on this dataset.
fields, from small projects to large car factories. However this
2.2 S. Houben, J. Stallkamp, J. Salmen,M. Schlipsing, and C.
topic also raises many questions and problems. It is required
Igel, “Detection of traffic signs in real-world images: The
to define the width of the edges of the road, recognize road
German traffic sign detection benchmark,” in Proc. IEEE
signs, traffic lights, pedestrians, and other objects which
IJCNN, 2013, pp. 1–8.
contribute the driving safely.
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