A Novel Detection and Recognition System for Chinese Traffic Signs

被引：0

作者：

Zhang Hanxizi ^{[1
]}

Wang Bo ^{[1
]}

Zheng Zhihui ^{[1
]}

Dai Yujie ^{[2
]}

机构：

[1] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China

[2] Beijing Inst Technol, Sch Mech Engn, Beijing 100081, Peoples R China

来源：

2013 32ND CHINESE CONTROL CONFERENCE (CCC) | 2013年

关键词：

Traffic signs; Detection and recognition system; White balance; LBP; SVM;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a novel detection and recognition system using an on-board single camera for Chinese traffic signs is proposed. First of all, image preprocessing method using white balance is adopted to weaken the effect of illumination changes. In the detection stage, sign candidates within Regions of Interest (ROIs) are detected by the combination of color and shape information. Then the uniform rotation-invariant Local Binary Patterns (LBP) and Support Vector Machine (SVM) are applied for the recognition stage. We have conducted lots of experiments in real road scenes and the results show that our system has high accuracy and good performance in clustered backgrounds.

引用

页码：8102 / 8107

页数：6

共 18 条

[1]

[Anonymous], ADV NEURAL INFORM PR

[2]

Barnes N, 2004, 2004 IEEE INTELLIGENT VEHICLES SYMPOSIUM, P566

[3] Real-time speed sign detection using the radial symmetry detector [J].

Barnes, Nick ;

Zelinsky, Alexander ;

Fletcher, Luke S. .

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2008, 9 (02) :322-332

[4]

Broggi Alberto, 2007, Proceedings of the 2007 IEEE Intelligent Vehicles Symposium, P981

[5]

Chen L, 2011, IEEE INT VEH SYM, P908, DOI 10.1109/IVS.2011.5940543

[6]

Chikane V, 2006, J INF SCI ENG, V22, P497

[7] Traffic sign recognition and analysis for intelligent vehicles [J].

de la Escalera, A ;

Armingol, JM ;

Mata, M .

IMAGE AND VISION COMPUTING, 2003, 21 (03) :247-258

[8]

Eichner ML, 2008, IEEE INT VEH SYM, P964

[9]

Garcia-Garrido M.A., 2006, IEEE INTELLIGENT TRA, P811

[10] P-N Learning: Bootstrapping Binary Classifiers by Structural Constraints [J].

Kalal, Zdenek ;

Matas, Jiri ;

Mikolajczyk, Krystian .

2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2010, :49-56

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