Real-time speed sign detection using the radial symmetry detector

被引:119
作者
Barnes, Nick [1 ,2 ]
Zelinsky, Alexander [3 ]
Fletcher, Luke S. [4 ]
机构
[1] Natl ICT Australia, Canberra, ACT 2600, Australia
[2] Australian Natl Univ, Dept Informat Engn, Canberra, ACT 0200, Australia
[3] Commonwealth Sci & Ind Res Organizat ICT Ctr, Canberra, ACT 0200, Australia
[4] MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USA
基金
澳大利亚研究理事会;
关键词
detection; fast radial symmetry; real time; road sign;
D O I
10.1109/TITS.2008.922935
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Algorithms for classifying road signs have a high computational cost per pixel processed. A detection stage that has a lower computational cost can facilitate real-time processing. Various authors have used shape and color-based detectors. Shape-based detectors have an advantage under variable lighting conditions and sign deterioration that, although the apparent color may change, the shape is preserved. In this paper, we present the radial symmetry detector for detecting speed signs. We evaluate the detector itself in a system that is mounted within a road vehicle. We also evaluate its performance that is integrated with classification over a series of sequences from roads around Canberra and demonstrate it while running online in our road vehicle. We show that it can detect signs with high reliability in real time. We examine the internal parameters of the algorithm to adapt it to road sign detection. We demonstrate the stability of the system under the variation of these parameters and show computational speed gains through their tuning. The detector is demonstrated to work under a wide variety of visual conditions.
引用
收藏
页码:322 / 332
页数:11
相关论文
共 32 条
  • [11] A real-time histographic approach to road sign recognition
    Estevez, L
    Kehtarnavaz, N
    [J]. PROCEEDINGS OF THE IEEE SOUTHWEST SYMPOSIUM ON IMAGE ANALYSIS AND INTERPRETATION, 1996, : 95 - 100
  • [12] Fang CY, 2003, PROC CVPR IEEE, P750
  • [13] Correlating driver gaze with the road scene for driver assistance systems
    Fletcher, L
    Loy, G
    Barnes, N
    Zelinsky, A
    [J]. ROBOTICS AND AUTONOMOUS SYSTEMS, 2005, 52 (01) : 71 - 84
  • [14] Recognition of traffic signs based on their colour and shape features extracted using human vision models
    Gao, X. W.
    Podladchikova, L.
    Shaposhnikov, D.
    Hong, K.
    Shevtsova, N.
    [J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2006, 17 (04) : 675 - 685
  • [15] GAVRILA DM, 1998, P INT C PATT REC AUG, P16
  • [16] Road sign detection and recognition using matching pursuit method
    Hsu, SH
    Huang, CL
    [J]. IMAGE AND VISION COMPUTING, 2001, 19 (03) : 119 - 129
  • [17] Kloeden C. N., 1997, 204 CR NHMRC ROAD AC
  • [18] Labayrade R, 2002, IV'2002: IEEE INTELLIGENT VEHICLE SYMPOSIUM, PROCEEDINGS, P646
  • [19] Lindner F, 2004, 2004 IEEE INTELLIGENT VEHICLES SYMPOSIUM, P49
  • [20] Fast radial symmetry for detecting points of interest
    Loy, G
    Zelinsky, A
    [J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2003, 25 (08) : 959 - 973