Comparative Survey on Traffic Sign Detection and Recognition: a Review

• Autorzy: Wali S. B. , Hannan M. A. , Hussain A. , Samad S. A.

Warianty tytułu

PL

Studium porównawcze metod detekcji i rozpoznawania znaków drogowych

• Języki publikacji: EN

Abstrakty

EN

Developing real-time Advanced Driver Assistance Systems (ADAS) based on video aiming to extract reliable vehicle state information has attracted a lot of attention during the past decades. This ADAS system includes inter-vehicle communication, driver behavioral monitoring, and human-machine interactions. In these systems, robust and reliable traffic sign detection and recognition (TSDR) technique is a critical step for ensuring vehicle safety. This paper provides a comprehensive survey on traffic sign detection and recognition system based on image and video data. Our main focus is to present the current trends and challenges in the field of developing an efficient TSDR system followed by a detail comparative study between different renowned methods used by various researchers. Finally, conclusion followed by some future suggestion is provided to develop an efficient TSDR system is provided. This survey will hopefully lead to develop an effective traffic sign detection and recognition system which will ensure driver safety in future.

PL

System ADAS (Advanced Driver Assistance System) obejmuje także metody rozpoznawania znaków drogowych. W artykule przedstawiono przegląd metod detekcji i rozpoznawania znaków drogowych bazujących na obrazie video. W artykule dokonano oceny istniejących metod oraz zaproponowano środki poprawy ich efektywności.

Słowa kluczowe

EN

traffic sign; detection; recognition; ADAS

PL

rozpoznawanie znaków drogowych; system ADAS; detekcja

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2015
• Tom: R. 91, nr 12
• Strony: 38--42
• Opis fizyczny: Bibliogr. 56 poz., rys., tab.

Twórcy

autor

Wali S. B.

• Dept. of Electrical, Electronic & Systems Engineering, Universiti Kebangsaan Malaysia, Malaysia

autor

Hannan M. A.

• Dept. of Electrical, Electronic & Systems Engineering, Universiti Kebangsaan Malaysia, Malaysia

autor

Hussain A.

• Dept. of Electrical, Electronic & Systems Engineering, Universiti Kebangsaan Malaysia, Malaysia

autor

Samad S. A.

• Dept. of Electrical, Electronic & Systems Engineering, Universiti Kebangsaan Malaysia, Malaysia

Bibliografia

• [1] Larsson F., Felsberg M., Using Fourier Descriptors and Spatial Models for Traffic Sign Recognition, Image Analysis Lecture Notes in Computer Science, 6688 (2011) 238–49.
• [2] Ren F.X., Huang J.S., Jiang R.Y., Klette R., General Traffic Sign Recognition by Feature Matching, (2009).
• [3] Ohgushi K., Hamada N., Traffic Sign Recognition by Bags of Features, IEEE Region 10 Conference, 1-4, (2009), 1352–7.
• [4] Gu Y.L., Yendo T., Tehrani M.P., Fujii T., Tanimoto M., Ieee., A New Vision System for Traffic Sign Recognition, 2010 IEEE Intelligent Vehicles Symposium (Iv), (2010) 7–12.
• [5] Paclik P., Novovicova J., Road Sign Classification without Color Information, Proceedings of the 6th Conference of Advanced School of Imaging and Computing, (2000).
• [6] Stallkamp J., Schlipsing M., Salmen J., Igel C., The German Traffic Sign Recognition Benchmark: A multi-class classification competition, The 2011 International Joint Conference on Neural Networks, (2011)1453–60.
• [7] Stallkamp J., Schlipsing M., Salmen J., Igel C., Man vs. computer: benchmarking machine learning algorithms for traffic sign recognition, Neural Networks : The Official Journal of the International Neural Network Society, 32 (2012) 323–32.
• [8] Timofte R., Zimmermann K., Gool L. Van., Multi-view traffic sign detection, recognition, and 3D localisation, 2009 Workshop on Applications of Computer Vision WACV, (2009) 1–8.
• [9] Grigorescu C., Petkov N., Distance sets for shape filters and shape recognition, IEEE Transactions on Image Processing : A Publication of the IEEE Signal Processing Society, 12 (2003) 1274–86.
• [10] Belaroussi R., Foucher P., Tarel J.-P., Soheilian B., Charbonnier P., Paparoditis N., Road Sign Detection in Images: A Case Study. 20th International Conference on Pattern Recognition (ICPR), (2010), 484–8.
• [11] Wali, Safat, Mohammad A Hannan, Shahrum abdullah, Aini Hussain S.A.S., Shape Matching and Color Segmentation Based Traffic Sign Detection System, PrzeglD Elektrotechniczny, 1 (2015) 38–42.
• [12] Hussain A., Hannan M.A., Mohamed A., Sanusi H., Ariffin A.K., Vehicle crash analysis for airbag deployment decision, International Journal of Automotive Technology, 7 (2006) 179–85.
• [13] Hannan M.A., Hussain A., Mohamed A., Samad S.A., Development of an embedded vehicle safety system for frontal crash detection. International Journal of Crashworthiness, 13 (2008) 579–87.
• [14] Safat B.W., Ridwanur R., Ahsan Z., J. Ahmed M., A Neural network Based System Architecture of An Automatic Traffic Sign Detection and Recognition System, Australian Journal of Basic and Applied Sciences, 8 (2013) 102–5.
• [15] Mohammad A Hannan, Safat Bin Wali, Tan J. Pin, Aini Hussain S.A.S., Traffic Sign Classification based on Neural Network for Advance Driver Assistance System, PrzeglD Elektrotechniczny, 1 (2014) 169–72.
• [16] Sheng Y.H., Zhang K., Ye C., Liang C., Li J., Automatic detection and recognition of traffic signs in stereo images based on features and probabilistic neural networks. In: Schelkens P, Ebrahimi T, Cristobal G, Truchetet F, editors. Optical and Digital Image Processing, vol. 7000, Bellingham: Spie-Int Soc Optical Engineering (2008).
• [17] S.K. Saha, D. Chakraborty M.A.A.B., Neural Network Based Traffic Sign Recognition, International Journal of Comput App, 50 (2012) 35–41.
• [18] Cireşan D., Meier U., Masci J., Schmidhuber J., Multi-column deep neural network for traffic sign classification, Neural Networks : The Official Journal of the International Neural Network Society, 32 (2012) 333–8.
• [19] Li Y., Pankanti S., Guan W., Real-Time Traffic Sign Detection: An Evaluation Study. 2010 20th International Conference on Pattern Recognition, (2010), 3033–6.
• [20] Chen L., Li Q., Li M., Zhang L., Mao Q., Design of a multisensor cooperation travel environment perception system for autonomous vehicle, Sensors, (Basel, Switzerland) 12 (2012) 12386–404.
• [21] Wu J., Tseng C., Chang C., Road sign recognition system based on GentleBoost with sharing features, IEEE International Conference on System Science and Engineering, (2011) 410–5.
• [22] Bascon S.M., Rodriguez J.A., Arroyo S.L., Caballero A.F., Lopez-Ferreras F., An optimization on pictogram identification for the road-sign recognition task using SVMs, Computer Vision and Image Understanding, 114 (2010) 373–83.
• [23] Garcia-Garrido M.A., Ocana M., Llorca D.F., Sotelo M.A., Arroyo E., Llamazares A., et al., Robust Traffic Signs Detection by means of Vision and V2I Communications, 2011 14th International IEEE Conference on Intelligent Transportation Systems, (2011), 1003–8.
• [24] A. Martinovic, G. Glavas, M. Juribasic, D. Sutic Z.K., Real-time detection and recognition of traffic sign, in Proc. IEEE 33rd Int. Convention MIPRO, (2010), 760–5.
• [25] Min K., Oh J., Kim B., Traffic sign extract and recognition on unmanned vehicle using image processing based on support vector machine, in Proc. IEEE 11th Int. Conf. on Control, Automation and Systems (ICCAS), (2011), 750–3.
• [26] Park J.-G., Kim K.-J., Design of a visual perception model with edge-adaptive Gabor filter and support vector machine for traffic sign detection, Expert Systems with Applications, 40 (2013) 3679–87.
• [27] Prieto M.S., Allen A.R., Using self-organising maps in the detection and recognition of road signs, Image and Vision Computing, 27 (2009) 673–83.
• [28] Khan J.F., Bhuiyan S.M. a., Adhami R.R., Image Segmentation and Shape Analysis for Road-Sign Detection, IEEE Transactions on Intelligent Transportation Systems, 12 (2011) 83–96.
• [29] Greenhalgh J., Mirmehdi M., Ieee., TRAFFIC SIGN RECOGNITION USING MSER AND RANDOM FORESTS. 2012 Proceedings of the 20th European Signal Processing Conference, Los Alamitos: Ieee Computer Soc; (2012), 1935–9.
• [30] Gonzalez-Reyna S.E., Avina-Cervantes J.G., Ledesma-Orozco S.E., Cruz-Aceves I., Eigen-Gradients for Traffic Sign Recognition, Mathematical Problems in Engineering, 2013 (2013) 6.
• [31] Pei D.L., Sun F.C., Liu H.P., Supervised Low-Rank Matrix Recovery for Traffic Sign Recognition in Image Sequences, IEEE Signal Processing Letters, 20 (2013) 241–4.
• [32] Wang W., Wei C.-H., Zhang L., Wang X., Traffic-signs recognition system based on multi-features, 2012 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA) Proceedings, (2012), 120–3.
• [33] Li L., Li J., Sun J., Robust traffic sign detection using fuzzy shape recognizer. In: Ding M, Bhanu B, Wahl FM, Roberts J, editors, in proc. Pattern Recognition and Computer vision, 7496 (2009), 74960Z – 74960Z – 8.
• [34] Pacl P., Novoviˇ J., Vitabile S., Gentile A., Sorbello F., Torresen J., et al., Real-Time Detection and Recognition of Road Traffic Signs, Robotics and Autonomous Systems, 13 (2012) 86–93.
• [35] Soheilian B., Paparoditis N., Vallet B., Detection and 3D reconstruction of traffic signs from multiple view color images, ISPRS Journal of Photogrammetry and Remote Sensing, 77 (2013) 1–20.
• [36] De la Escalera A., Armingol J.M., Mata M., Traffic sign recognition and analysis for intelligent vehicles, Image and Vision Computing, 21 (2003) 247–58.
• [37] Hechri A., Mtibaa A., Automatic Detection and Recognition of Road Sign for Driver Assistance System, 2012 16th IEEE Mediterranean Electrotechnical Conference,(2012), 888–91.
• [38] Gil-Jimenez P., Lafuente-Arroyo S., Maldonado-Bascon S., Gomez-Moreno H., Shape classification algorithm using support vector machines for traffic sign recognition. In: Cabestany J, Prieto A, Sandoval F, editors. Computational Intelligence and Bioinspired Systems, Proceedings, vol. 3512, Berlin: Springer-Verlag Berlin; (2005), 873–80.
• [39] Prisacariu V.A., Timofte R., Zimmermann K., Reid I., Gool L. Van., Integrating Object Detection with 3D Tracking Towards a Better Driver Assistance System, 2010 20th International Conference on Pattern Recognition, (2010), 3344–7.
• [40] Xie Y., Liu L., Li C., Qu Y., Unifying visual saliency with HOG feature learning for traffic sign detection, 2009 IEEE Intelligent Vehicles Symposium, (2009), 24–9.
• [41] Gao X.W., Podladchikova L., Recognition of traffic signs based on their colour and shape features extracted using human vision models, Journal of Visual Communication and Image Representation, 17 (2006) 675–85.
• [42] Soheilian B., Paparoditis N., Vallet B., Detection and 3D reconstruction of traffic signs from multiple view color images, Isprs Journal of Photogrammetry and Remote Sensing, 77 (2013) 1–20.
• [43] Khan J.F., Adhami R.R., Bhuiyan S.M.A., Ieee., Image Segmentation based Road Sign Detection, Proceedings of IEEE the Southeastcon 2009, (2009), 24–9.
• [44] Huang Y.-S., Le Y.-S., Cheng F.-H., A Method of Detecting and Recognizing Speed-limit Signs, 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, (2012), 371–4.
• [45] K-H. Jo and A. Vavilin., HDR Image Generation based on Intensity Clustering and Local Feature Analysis, Computers in Human Behavior, 27 (2011) 1507–11.
• [46] A. Vavilin and K-H. Jo., Automatic Context Analysis for Image Classification and Retrieval, Proc. Int’l Conference on Intelligent Computing, Lecture Note of Computer Science, (2011), 377–83.
• [47] A. Vavilin and K-H. Jo., Automatic Context Analysis for Image Classification and Retrieval based on Optimal Feature Subset Selection, Neurocomputing, 1 (2013) 201–107.
• [48] Azzopardi G., Petkov N., Trainable COSFIRE Filters for Keypoint Detection and Pattern Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, 35 (2013) 490–503.
• [49] Yang L., Kwon K.-R., Moon K., Lee S.-H., Kwon S.-G., Broken traffic sign recognition based on local histogram matching, 2012 IEEE Computing, Communications and Applications Conference, (2012), 415–9.
• [50] Mogelmose A., Trivedi M.M., Moeslund T.B., Vision-Based Traffic Sign Detection and Analysis for Intelligent Driver Assistance Systems: Perspectives and Survey, IEEE Transactions on Intelligent Transportation Systems, 13 (2012) 1484–97.
• [51] Markus Mathias, Radu Timofte, Rodrigo Benenson L.V.G., Traffic sign Recognition: How far we from solution, International Joint Conference on Neural Networks, (2013), 1–8.
• [52] Fu M.Y., Huang Y.S., A Survey of Traffic Sign Recognition, Proceedings of the 2010 International Conference on Wavelet Analysis and Pattern Recognition, (2010), p. 119–24.
• [53] Nguwi Y. -y., Kouzani A.Z., A Study on Automatic Recognition of Road Signs, 2006 IEEE Conference on Cybernetics and Intelligent Systems, (2006), p. 1–6.
• [54] Mammeri A., Boukerche A., Almulla M., Design of traffic sign detection, recognition, and transmission systems for smart vehicles, IEEE Wireless Communications, 20 (2013) 36–43.
• [55] Gomez-Moreno H., Maldonado-Bascon S., Gil-Jimenez P., Lafuente-Arroyo S., Goal Evaluation of Segmentation Algorithms for Traffic Sign Recognition, IEEE Transactions on Intelligent Transportation Systems, 11 (2010) 917–30.
• [56] Gonzalez A., Bergasa L.M., Yebes J.J., Text Detection and Recognition on Traffic Panels From Street-Level Imagery Using Visual Appearance, IEEE Transactions on Intelligent Transportation Systems, 15 (2014) 228–38.