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IJSTR >> Volume 5 - Issue 6, June 2016 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Real-Time Traffic Sign Recognition using SURF Descriptor

[Full Text]

 

AUTHOR(S)

Htet Wai Kyu, Lu Maw, Hla Myo Tun

 

KEYWORDS

color segmentation, Hough circle, traffic sign, SURF

 

ABSTRACT

For road safety, traffic sign is essential for drivers by giving valuable safety and navigation information, pedestrians and even for the development of autonomous driver assistance system. Traffic sign can be classified by two methods can be approached. First approach is color base segmentation which is the region of traffic sign by using HSV color space (Hue, Saturation and Value) and the next approach is shape base segmentation using Hough Circle Detection. In thissystem, we use circle shape base detection for every traffic sign. At first, keypoints descriptor is extracted from each standard traffic sign image in database and then keypoints descriptor is taken from region of traffic sign extracted from Hough circle detection. After that, the nearest distance is matched keypoints descriptor between in each standard traffic sign image in database and extracted traffic sign image.

 

REFERENCES

[1] Jou-an, Lin and Shih-Hong, Chio:” Automatic Recognition of Traffic Signs from Vehicle-Borne Images”, Dept.of Land Economics, n0.64, Sec.2

[2] A.Martinovic,G.Glavas,M.Juribasic,D.Suticand Z.Kalafatic,”Real-time Detection and Recognition of Traffic Signs” ,Faculty of Electrical Engineering and Computing , Unska ,10000 Zagreb

[3] Andrzej Ruta, Fatih Porikli, Shintaro Watanabe, YongminLi,”In-vehicle camera traffic sign detection and recognition”, Machine Vision and Applications, DOI 10.1007/s00138-009-0231-x

[4] Krzysztof Dyczkowski ,Pawel Gadecki, AdamKulakowski,”Traffic Signs Recognition System”,Faulty of Mathematics and Computer Science,Adam Mickiewicz University,Umultowska 87,61-614 poznan,Poland

[5] Karla Brkic,”An Overview Of Traffic Sign Detection Methods” ,Faculty of Electrical Engineering and Computing , Unska 3 ,10000 Zagreb,Croatia