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An overview of traffic sign detection and classification methods

  • Yassmina SaadnaEmail author
  • Ali Behloul
Trends and Surveys

Abstract

Over the last few years, different traffic sign recognition systems were proposed. The present paper introduces an overview of some recent and efficient methods in the traffic sign detection and classification. Indeed, the main goal of detection methods is localizing regions of interest containing traffic sign, and we divide detection methods into three main categories: color-based (classified according to the color space), shape-based, and learning-based methods (including deep learning). In addition, we also divide classification methods into two categories: learning methods based on hand-crafted features (HOG, LBP, SIFT, SURF, BRISK) and deep learning methods. For easy reference, the different detection and classification methods are summarized in tables along with the different datasets. Furthermore, future research directions and recommendations are given in order to boost TSR’s performance.

Keywords

Traffic sign detection Traffic sign classification Image processing Object detection Vehicle safety 

References

  1. 1.
    Gudigar A, Chokkadi S, Raghavendra U (2016) A review on automatic detection and recognition of traffic sign. Multimed Tools Appl 75(1):333–364CrossRefGoogle Scholar
  2. 2.
    Fu MY, Huang YS (2010) A survey of traffic sign recognition. In: International conference on wavelet analysis and pattern recognition (ICWAPR), 2010, IEEE, pp 119–124Google Scholar
  3. 3.
    Wali SB, Hannan MA, Hussain A, Samad SA (2015) Comparative survey on traffic sign detection and recognition: a review. Przegld Elektrotechniczny, ISSN: 0033-2097Google Scholar
  4. 4.
    Escalera S, Bar X, Pujol O, Vitri J, Radeva P (2011) Background on traffic sign detection and recognition. In: Traffic-sign recognition systems. Springer, London, pp 5–13Google Scholar
  5. 5.
    De La Escalera A, Moreno LE, Salichs MA, Armingol JM (1997) Road traffic sign detection and classification. IEEE Trans Indus Electron 44(6):848–859CrossRefGoogle Scholar
  6. 6.
    Benallal M, Meunier J (2003) Real-time color segmentation of road signs. In: Canadian conference on electrical and computer engineering, vol 3, 2003, IEEE CCECE 2003, IEEE, pp 1823–1826Google Scholar
  7. 7.
    Ruta A, Li Y, Liu X (2010) Real-time traffic sign recognition from video by class-specific discriminative features. Pattern Recogn 43(1):416–430CrossRefzbMATHGoogle Scholar
  8. 8.
    Ruta A, Porikli F, Watanabe S, Li Y (2011) In-vehicle camera traffic sign detection and recognition. Mach Vis Appl 22(2):359–375CrossRefGoogle Scholar
  9. 9.
    Lim KH, Ang LM, Seng KP (2009) New hybrid technique for traffic sign recognition. In: International symposium on intelligent signal processing and communications systems, 2008. ISPACS 2008, IEEE, pp 1–4Google Scholar
  10. 10.
    Itti L, Koch C, Niebur E (1998) A model of saliency-based visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell 20(11):1254–1259CrossRefGoogle Scholar
  11. 11.
    Behloul A, Saadna Y (2014) A Fast and Robust Traffic Sign Recognition. Int J Innov Appl Stud 5(2):139Google Scholar
  12. 12.
    Yakimov P (2015) Traffic signs detection using tracking with prediction. In: International conference on E-business and telecommunications Colmar, France, Springer, pp 454–467Google Scholar
  13. 13.
    Yakimov PY (2015) Preprocessing digital images for quickly and reliably detecting road signs. Pattern Recogn Image Anal 25(4):729–732CrossRefGoogle Scholar
  14. 14.
    Wang G, Ren G, Jiang L, Quan T (2014) Hole-based traffic sign detection method for traffic signs with red rim. Vis Comput 30(5):539–551CrossRefGoogle Scholar
  15. 15.
    Mogelmose A, Trivedi MM, Moeslund TB (2012) Vision-based traffic sign detection and analysis for intelligent driver assistance systems: Perspectives and survey. IEEE Trans Intell Transp Syst 13(4):1484–1497CrossRefGoogle Scholar
  16. 16.
    Maldonado-Bascon S, Lafuente-Arroyo S, Gil-Jimenez P, Gomez-Moreno H, Lpez-Ferreras F (2007) Road-sign detection and recognition based on support vector machines. IEEE Trans Intell Transp Syst 8(2):264–278CrossRefGoogle Scholar
  17. 17.
    Fleyeh H (2006) Shadow and highlight invariant color segmentation algorithm for traffic signs. In: IEEE conference on cybernetics and intelligent systems, 2006, IEEE, pp 1–7Google Scholar
  18. 18.
    Vitabile S, Pollaccia G, Pilato G, Sorbello F (2001) Road signs recognition using a dynamic pixel aggregation technique in the HSV color space. In: Proceedings of the 11th international conference on image analysis and processing, 2001, IEEE, pp 572–577Google Scholar
  19. 19.
    De la Escalera A, Armingol JM, Mata M (2003) Traffic sign recognition and analysis for intelligent vehicles. Image Vis Comput 21(3):247–258CrossRefGoogle Scholar
  20. 20.
    Fang CY, Fuh CS, Yen PS, Cherng S, Chen SW (2004) An automatic road sign recognition system based on a computational model of human recognition processing. Comput Vis Image Underst 96(2):237–268CrossRefGoogle Scholar
  21. 21.
    Miura J, Kanda T, Nakatani S, Shirai Y (2002) An active vision system for on-line traffic sign recognition. IEICE TRANSACTIONS on Inf Syst 85(11):1784–1792Google Scholar
  22. 22.
    Broggi A, Cerri P, Medici P, Porta PP, Ghisio G (2007) Real time road signs recognition. In: IEEE intelligent vehicles symposium, 2007, IEEE, pp 981–986Google Scholar
  23. 23.
    Gmez-Moreno H, Maldonado-Bascn S, Gil-Jimnez P, Lafuente-Arroyo S (2010) Goal evaluation of segmentation algorithms for traffic sign recognition. IEEE Trans Intell Transp Syst 11(4):917–930CrossRefGoogle Scholar
  24. 24.
    Liu C, Chang F, Chen Z, Liu D (2016) Fast traffic sign recognition via high-contrast region extraction and extended sparse representation. IEEE Trans Intell Transp Syst 17(1):79–92CrossRefGoogle Scholar
  25. 25.
    Hechri A, Hmida R, Mtibaa A (2015) Robust road lanes and traffic signs recognition for driver assistance system. Int J Comput Sci Eng 10(1–2):202–209CrossRefGoogle Scholar
  26. 26.
    Garcia-Garrido MA, Sotelo MA, Martin-Gorostiza E (2006) Fast traffic sign detection and recognition under changing lighting conditions. In: IEEE intelligent transportation systems conference, 2006 ITSC’06, IEEE, pp. 811–816Google Scholar
  27. 27.
    Barnes N, Zelinsky A (2004) Real-time radial symmetry for speed sign detection. In: IEEE intelligent vehicles symposium, 2004, IEEE, pp 566–571Google Scholar
  28. 28.
    Loy G, Barnes N (2004) Fast shape-based road sign detection for a driver assistance system. In: Proceedings of the 2004 IEEE/RSJ international conference on intelligent robots and systems, 2004 (IROS 2004) Vol 1, IEEE, pp 70-75Google Scholar
  29. 29.
    Soheilian B, Arlicot A, Paparoditis N (2010) Extraction de panneaux de signalisation routire dans des images couleurs. In: Reconnaissance des Formes et Intelligence Artificielle, pp 1–8Google Scholar
  30. 30.
    Zhang SC, Liu ZQ (2005) A robust, real-time ellipse detector. Pattern Recogn 38(2):273–287MathSciNetCrossRefzbMATHGoogle Scholar
  31. 31.
    Larsson F, Felsberg M (2011) Using Fourier descriptors and spatial models for traffic sign recognition. In: Scandinavian conference on image analysis, Springer, Berlin, Heidelberg, pp 238–249Google Scholar
  32. 32.
    Qin F, Fang B, Zhao H (2010) Traffic sign segmentation and recognition in scene images. In: Chinese conference on pattern recognition (CCPR), pp 1–5Google Scholar
  33. 33.
    Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE computer society conference on computer vision and pattern recognition, CVPR 2001, vol 1, IEEE, p IGoogle Scholar
  34. 34.
    Brkic K, Pinz A, \(\check{\rm S}\)egvic S (2009) Traffic sign detection as a component of an automated traffic infrastructure inventory system. Stainz, AustriaGoogle Scholar
  35. 35.
    Brki K , \(\check{\rm S}\)egvi S, Kalafati Z, Sikiri I, Pinz A (2010) Generative modeling of spatio-temporal traffic sign trajectories. In: IEEE computer society conference on computer vision and pattern recognition workshops (CVPRW), 2010, IEEE, pp 25–31Google Scholar
  36. 36.
    Brkic K (2010) An overview of traffic sign detection methods. Department of Electronics, Microelectronics, Computer and Intelligent Systems Faculty of Electrical Engineering and Computing Unska, 3, 10000Google Scholar
  37. 37.
    Bar X, Escalera S, Vitri J, Pujol O, Radeva P (2009) Traffic sign recognition using evolutionary adaboost detection and forest-ECOC classification. IEEE Trans Intell Transp Syst 10(1):113–126CrossRefGoogle Scholar
  38. 38.
    Prisacariu VA, Timofte R, Zimmermann K, Reid I, Van Gool L (2010) Integrating object detection with 3d tracking towards a better driver assistance system. In: 20th International conference on pattern recognition (ICPR), 2010, IEEE, pp 3344–3347Google Scholar
  39. 39.
    Fang CY, Chen SW, Fuh CS (2003) Road-sign detection and tracking. IEEE Trans Veh Technol 52(5):1329–1341CrossRefGoogle Scholar
  40. 40.
    Zaklouta F, Stanciulescu B (2011) Warning traffic sign recognition using a HOG-based Kd tree. In: IEEE intelligent vehicles symposium (IV), 2011. IEEE, pp 1019–1024Google Scholar
  41. 41.
    Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: IEEE computer society conference on computer vision and pattern recognition, CVPR 2005, vol 1, IEEE pp 886–893Google Scholar
  42. 42.
    Wang G, Ren G, Wu Z, Zhao Y, Jiang L (2013) A robust, coarse-to-fine traffic sign detection method. In: The 2013 international joint conference on neural networks (IJCNN), IEEE, pp 1–5Google Scholar
  43. 43.
    Houben S, Stallkamp J, Salmen J, Schlipsing M, Igel C (2013) Detection of traffic signs in real-world images: The German Traffic Sign Detection Benchmark. In: The 2013 international joint conference on neural networks (IJCNN), IEEE, pp 1–8Google Scholar
  44. 44.
    Houben S (2011) A single target voting scheme for traffic sign detection. In: IEEE intelligent vehicles symposium (IV), 2011, IEEE, pp 124–129Google Scholar
  45. 45.
    Mathias M, Timofte R, Benenson R, Van Gool L (2013) Traffic sign recognitionHow far are we from the solution?. In: The 2013 international joint conference on neural networks (IJCNN), IEEE, pp 1–8Google Scholar
  46. 46.
    Wu Y, Liu Y, Li J, Liu H, Hu X (2013) Traffic sign detection based on convolutional neural networks. In: The 2013 international joint conference on neural networks (IJCNN), pp 1–7, IEEEGoogle Scholar
  47. 47.
    Liu C, Chang F, Chen Z, Li S (2013) Rapid traffic sign detection and classification using categories-first-assigned tree. J Comput Inf Syst 9(18):7461–7468Google Scholar
  48. 48.
    Liu C, Chang F, Chen Z (2014) Rapid multiclass traffic sign detection in high-resolution images. IEEE Trans Intell Transp Syst 15(6):2394–2403CrossRefGoogle Scholar
  49. 49.
    Timofte R, Zimmermann K, Van Gool L (2009) Multi-view traffic sign detection, recognition, and 3d localisation. In: Workshop on applications of computer vision (WACV), 2009, IEEE, pp 1–8Google Scholar
  50. 50.
    Mogelmose A, Trivedi MM, Moeslund TB (2012) Learning to detect traffic signs: comparative evaluation of synthetic and real-world datasets. In: 21st International conference on pattern recognition (ICPR), 2012, IEEE, pp 3452–3455Google Scholar
  51. 51.
    \(\check{\rm S}\)egvic S, Brki K, Kalafati Z, Stanisavljevi V, evrovi M, Budimir D, Dadi I (2010) A computer vision assisted geoinformation inventory for traffic infrastructure. In: 13th International IEEE conference on intelligent transportation systems (ITSC), 2010, IEEE, pp 66–73Google Scholar
  52. 52.
    Zaklouta F, Stanciulescu, B., Hamdoun, O. (2011) Traffic sign classification using kd trees and random forests. In: The 2011 international joint conference on neural networks (IJCNN), pp 2151–2155, IEEEGoogle Scholar
  53. 53.
    Stallkamp J, Schlipsing M, Salmen J, Igel C (2012) Man vs. computer: benchmarking machine learning algorithms for traffic sign recognition. Neural networks 32:323–332CrossRefGoogle Scholar
  54. 54.
    Sermanet P, LeCun Y (2011) Traffic sign recognition with multi-scale convolutional networks. In The 2011 international joint conference on neural networks (IJCNN), IEEE, pp 2809–2813Google Scholar
  55. 55.
    Cirean D, Meier U, Masci J, Schmidhuber J (2011) A committee of neural networks for traffic sign classification. In: The 2011 international joint conference on neural networks (IJCNN), IEEE, pp 1918–1921Google Scholar
  56. 56.
    CireAn D, Meier U, Masci J, Schmidhuber J (2012) Multi-column deep neural network for traffic sign classification. Neural Netw 32:333–338CrossRefGoogle Scholar
  57. 57.
    Zeng Y, Xu X, Fang Y, Zhao K (2015) Traffic sign recognition using extreme learning classifier with deep convolutional features. In: The 2015 international conference on intelligence science and big data engineering (IScIDE 2015), Suzhou, ChinaGoogle Scholar
  58. 58.
    Aghdam HH, Heravi EJ, Puig D (2017) A practical and highly optimized convolutional neural network for classifying traffic signs in real-time. Int J Comput Vis 122(2):246–269MathSciNetCrossRefGoogle Scholar
  59. 59.
    Ciregan D, Meier U, Schmidhuber J (2012) Multi-column deep neural networks for image classification. In IEEE conference on computer vision and pattern recognition (CVPR), 2012, IEEE, pp 3642–3649Google Scholar
  60. 60.
    Jin J, Fu K, Zhang C (2014) Traffic sign recognition with hinge loss trained convolutional neural networks. IEEE Trans Intell Transp Syst 15(5):1991–2000CrossRefGoogle Scholar
  61. 61.
    Yakimov PY (2016) Real-time road signs recognition using mobile GPU. In: CEUR workshop proceedings, vol 1638, pp 477–483Google Scholar
  62. 62.
    Qu Y, Yang S, Wu W, Lin L (2016) Hierarchical traffic sign recognition. In: Pacific rim conference on multimedia, Springer, pp 200–209Google Scholar
  63. 63.
    Abedin MZ, Dhar P, Deb K (2016) Traffic Sign Recognition using SURF: speeded up robust feature descriptor and artificial neural network classifier. In: 9th International conference on electrical and computer engineering (ICECE), 2016, IEEE, pp 198–201Google Scholar
  64. 64.
    Han Y, Virupakshappa K, Oruklu E (2015) Robust traffic sign recognition with feature extraction and k-NN classification methods. In: IEEE international conference on electro/information technology (EIT), 2015, IEEE, pp 484–488Google Scholar
  65. 65.
    Malik Z, Siddiqi I (2014) Detection and recognition of traffic signs from road scene images. In: 12th International conference on frontiers of information technology (FIT), 2014, IEEE, pp 330–335Google Scholar
  66. 66.
    Sathish P, Bharathi D (2016) Automatic road sign detection and recognition based on SIFT feature matching algorithm. In: Proceedings of the international conference on soft computing systems. Springer India, pp 421–431Google Scholar
  67. 67.
    Hua X, Zhua X, Lia D, Li H (2010) Traffic sign recognition using Scale invariant feature transform and SVM. In: A special joint symposium of ISPRS technical commission IV and AutoCarto in conjunction with ASPRS/CaGIS fall specialty conference November, pp 15–19Google Scholar
  68. 68.
    Lasota M, Skoczylas M (2016) Recognition of multiple traffic signs using keypoints feature detectors. In: International conference and exposition on electrical and power engineering (EPE), 2016, IEEE, pp 535–540Google Scholar
  69. 69.
    Chen L, Li Q, Li M, Mao Q (2011) Traffic sign detection and recognition for intelligent vehicle. In: IEEE intelligent vehicles symposium (IV), 2011, IEEE, pp 908–913Google Scholar
  70. 70.
    Hoferlin B, Zimmermann K (2009) Towards reliable traffic sign recognition. In: IEEE Intelligent vehicles symposium, 2009, IEEE, pp 324–329Google Scholar
  71. 71.
    Liu H, Liu Y, Sun F (2014) Traffic sign recognition using group sparse coding. Inf Sci 266:75–89CrossRefGoogle Scholar
  72. 72.
    He X, Dai B (2016) A new traffic signs classification approach based on local and global features extraction. In: International conference on information communication and management (ICICM), IEEE, pp 121–125Google Scholar
  73. 73.
    Tang S, Huang LL (2013) Traffic sign recognition using complementary features. In: 2nd IAPR Asian conference on pattern recognition (ACPR), 2013, IEEE, pp 210–214Google Scholar
  74. 74.
    Li C, Yang C (2016) The research on traffic sign recognition based on deep learning. In: 16th International symposium on communications and information technologies (ISCIT), 2016, IEEE, pp 156–161Google Scholar
  75. 75.
    Akinlar C, Topal C (2013) EDCircles: a real-time circle detector with a false detection control. Pattern Recogn 46(3):725–740CrossRefGoogle Scholar
  76. 76.
    Berkaya SK, Gunduz H, Ozsen O, Akinlar C, Gunal S (2016) On circular traffic sign detection and recognition. Expert Syst Appl 48:67–75CrossRefGoogle Scholar
  77. 77.
    Aghdam HH, Heravi EJ, Puig D (2016) A practical approach for detection and classification of traffic signs using Convolutional Neural Networks. Robot Auton Syst 84:97–112CrossRefGoogle Scholar
  78. 78.
    Aghdam HH, Heravi EJ, Puig D (2016) Recognizing traffic signs using a practical deep neural network. In: Robot 2015: 2nd Iberian robotics conference, Springer, pp 399–410Google Scholar
  79. 79.
    Maas AL, Hannun AY, Ng AY (2013) Rectifier nonlinearities improve neural network acoustic models. In: Proceedings of the ICML, vol 30, No 1Google Scholar
  80. 80.
    Eickeler S, Valdenegro M, Werner T, Kieninger M (2016) Future computer vision algorithms for traffic sign recognition systems. In: Advanced microsystems for automotive applications 2015, Springer, pp 69–77Google Scholar
  81. 81.
    Youssef A, Albani D, Nardi D, Bloisi DD (2016) Fast traffic sign recognition using color segmentation and deep convolutional networks. In: International conference on advanced concepts for intelligent vision systems, Springer, pp 205–216Google Scholar
  82. 82.
    Huang Z, Yu Y, Gu J, Liu H (2016) An efficient method for traffic sign recognition based on extreme learning machine. IEEE Trans Cybern 47(4):920–933CrossRefGoogle Scholar
  83. 83.
    Zang D, Zhang J, Zhang D, Bao M, Cheng J, Tang K (2016) Traffic sign detection based on cascaded convolutional neural networks. In: 17th IEEE/ACIS international conference on software engineering, artificial intelligence, networking and parallel/distributed computing (SNPD), 2016, IEEE, pp 201–206Google Scholar
  84. 84.
    Salti S, Petrelli A, Tombari F, Fioraio N, Di Stefano L (2015) Traffic sign detection via interest region extraction. Pattern Recogn 48(4):1039–1049CrossRefGoogle Scholar
  85. 85.
    Chen T, Lu S (2016) Accurate and efficient traffic sign detection using discriminative adaboost and support vector regression. IEEE Trans Veh Technol 65(6):4006–4015CrossRefGoogle Scholar
  86. 86.
    Ellahyani A, El Ansari M, El Jaafari I (2016) Traffic sign detection and recognition based on random forests. Appl Soft Comput 46:805–815CrossRefGoogle Scholar
  87. 87.
    Qian R, Yue Y, Coenen F, Zhang B (2016) Traffic sign recognition with convolutional neural network based on max pooling positions. In: 12th International conference on natural computation, fuzzy systems and knowledge discovery (ICNC-FSKD), 2016, IEEE, pp 578–582Google Scholar
  88. 88.
    Xie K, Ge S, Ye Q, Luo Z (2016) Traffic sign recognition based on attribute-refinement cascaded convolutional neural networks. In: Pacific rim conference on multimedia, Springer, pp 201–210Google Scholar
  89. 89.
    Aghdam HH, Heravi EJ, Puig D (2015) Traffic sign recognition using visual attributes and Bayesian network. In: International joint conference on computer vision, imaging and computer graphics, Springer, pp 295–315Google Scholar

Copyright information

© Springer-Verlag London 2017

Authors and Affiliations

  1. 1.LaSTIC Laboratory, Department of Computer ScienceUniversity of Batna 2BatnaAlgeria

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