Traffic Sign Detection based on Color Segmentation of Obscure Image Candidates: A Comprehensive Study

Full Text (PDF, 584KB), PP.35-46

Views: 0 Downloads: 0

Author(s)

Dip Nandi 1,* A. F. M. Saifuddin Saif 2 Prottoy Paul 2 Kazi Md. Zubair 2 Seemanta Ahmed Shubho 2

1. American International University-Bangladesh, Faculty of Science and Information Technology Dhaka, 1212, Bangladesh

2. American International University-Bangladesh, Faculty of Science & Information Technology Dhaka, 1212, Bangladesh

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2018.06.05

Received: 11 Apr. 2018 / Revised: 29 Apr. 2018 / Accepted: 17 May 2018 / Published: 8 Jun. 2018

Index Terms

Color-based detection, Shape-based detection, Uncontrolled Environment, Multi-class classification

Abstract

Automated Vehicular System has become a necessity in the current technological revolution. Real Traffic sign detection and recognition is a vital part of that system that will find roadside traffic signs to warn the automated system or driver beforehand of the physical conditions of roads. Mostly, researchers based on Traffic sign detection face problems such as locating the sign, classifying it and distinguishing one sign from another. The most common approach for locating and detecting traffic signs is the color information extraction method. The accuracy of color information extraction is dependent upon the selection of a proper color space and its capability to be robust enough to provide color analysis data. Techniques ranging from template matching to critical Machine Learning algorithms are used in the recognition process. The main purpose of this research is to give a review based on methods and framework of Traffic Sign Detection and Recognition solution and discuss also the current challenges of the whole solution.

Cite This Paper

Dip Nandi, A.F.M. Saifuddin Saif, Prottoy Paul, Kazi Md. Zubair, Seemanta Ahmed Shubho, " Traffic Sign Detection based on Color Segmentation of Obscure Image Candidates: A Comprehensive Study", International Journal of Modern Education and Computer Science(IJMECS), Vol.10, No.6, pp. 35-46, 2018. DOI:10.5815/ijmecs.2018.06.05

Reference

[1]P. Paclı́k, J. Novovičová, P. Pudil and P. Somol, "Road sign classification using Laplace kernel classifier", Pattern Recognition Letters, vol. 21, no. 13-14, pp. 1165-1173, 2000.
[2]M. Prieto and A. Allen, "Using self-organizing maps in the detection and recognition of road signs", Image and Vision Computing, vol. 27, no. 6, pp. 673-683, 2009.
[3]De la Escalera, J. Armingol and M. Mata, "Traffic sign recognition and analysis for intelligent vehicles", Image and Vision Computing, vol. 21, no. 3, pp. 247-258, 2003.
[4]M.Benallal and J. Meunier, "Real-time color segmentation of road signs", CCECE 2003 - Canadian Conference on Electrical and Computer Engineering. Toward a Caring and Humane Technology (Cat. No.03CH37436), vol. 3, pp.:1823- 1826, 2003.
[5]M. M. Zadeh, T. Kasvand, and C. Y. Suen, "Localization and recognition of traffic signs for automated vehicle control systems", In Proc. SPIE Vol. 3207, Intelligent Transportation Systems, pages 272–282, 1998.
[6]A. de la Escalera, L. Moreno, M. Salichs and J. Armingol, "Road traffic sign detection and classification", IEEE Transactions on Industrial Electronics, vol. 44, no. 6, pp. 848-859, 1997.
[7]C. Bahlmann, Y. Zhu, Visvanathan Ramesh, M. Pellkofer and T. Koehler, "A system for traffic sign detection, tracking, and recognition using color, shape, and motion information", IEEE Proceedings. Intelligent Vehicles Symposium, 2005., pp. 255-260, 2005.
[8]S. Maldonado-Bascon, S. Lafuente-Arroyo, P. Gil-Jimenez, H. Gomez-Moreno and F. Lopez-Ferreras, "Road-Sign Detection and Recognition Based on Support Vector Machines", IEEE Transactions on Intelligent Transportation Systems, vol. 8, no. 2, pp. 264-278, 2007.
[9]R. Malik, J. Khurshid and S. Ahmad, "Road Sign Detection and Recognition using Color Segmentation, Shape Analysis, and Template Matching", 2007 International Conference on Machine Learning and Cybernetics, vol. 6, pp. 3556-3560, 2007.
[10]H. Huang, C. Chen, Y. Jia and S. Tang, "Automatic Detection and Recognition of Circular Road Sign", 2008 IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, pp. 626–630, 2008.
[11]P. Wanitchai and S. Phiphobmongkol, "Traffic Warning Signs Detection and Recognition Based on Fuzzy Logic and Chain Code Analysis", 2008 Second International Symposium on Intelligent Information Technology Application, pp. 508- 512, 2008.
[12]K. C.G., L. Prabhu, A. V. and R. K., "Traffic Sign Detection and Pattern Recognition Using Support Vector Machine", 2009 Seventh International Conference on Advances in Pattern Recognition, pp. 87- 90, 2009.
[13]W. Shadeed, D. Abu-Al-Nadi, and M. Mismar, "Road traffic sign detection in color images", 10th IEEE International Conference on Electronics, Circuits, and Systems, 2003. ICECS 2003. Proceedings of 2003, vol. 2, pp. 890 - 893, 2003.
[14]S. Vitabile, G. Pollaccia, G. Pilato and E. Sorbello, "Road signs recognition using a dynamic pixel aggregation technique in the HSV color space", Proceedings 11th International Conference on Image Analysis and Processing, pp. 572- 577, 2001.
[15]X. Gao, L. Podladchikova, D. Shaposhnikov, K. Hong and N. Shevtsova, "Recognition of traffic signs based on their color and shape features extracted using human vision models", Journal of Visual Communication and Image Representation, vol. 17, no. 4, pp. 675-685, 2006.
[16]P P. Paclík and J. Novovičová, "Road Sign Recognition without Color Information", in 6th Annual Conference of the Advances School for Computing and Imaging Conference, ASCI 2000, Belgium, 2000, pp. 84-90.
[17]G. Loy and N. Barnes, "Fast shape-based road sign detection for a driver assistance system," 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566), 2004, pp. 70-75 vol.1.
[18]S. Chakraborty and K. Deb, "Bangladeshi road sign detection based on YCbCr color model and DtBs vector," 2015 International Conference on Computer and Information Engineering (ICCIE), Rajshahi, 2015, pp. 158-161.
[19]Z. Malik and I. Siddiqi, "Detection and Recognition of Traffic Signs from Road Scene Images," 2014 12th International Conference on Frontiers of Information Technology, Islamabad, 2014, pp. 330-335.
[20]C. Liu, F. Chang, Z. Chen and D. Liu, "Fast Traffic Sign Recognition via High-Contrast Region Extraction and Extended Sparse Representation," in IEEE Transactions on Intelligent Transportation Systems, vol. 17, no. 1, pp. 79-92, Jan. 2016.
[21]S. Maldonado-Bascon, S. Lafuente-Arroyo, P. Siegmann, H. Gomez-Moreno and F. J. Acevedo-Rodriguez, "Traffic sign recognition system for inventory purposes," 2008 IEEE Intelligent Vehicles Symposium, Eindhoven, 2008, pp. 590-595.
[22]J. Greenhalgh and M. Mirmehdi, "Real-Time Detection and Recognition of Road Traffic Signs," in IEEE Transactions on Intelligent Transportation Systems, vol. 13, no. 4, pp. 1498-1506, Dec. 2012.
[23]S. Maldonado-Bascon, S. Lafuente-Arroyo, P. Gil-Jimenez, H. Gomez-Moreno and F. Lopez-Ferreras, "Road-Sign Detection and Recognition Based on Support Vector Machines," in IEEE Transactions on Intelligent Transportation Systems, vol. 8, no. 2, pp. 264-278, June 2007.
[24]Sin-Yu Chen and Jun-Wei Hsieh, "Boosted road sign detection and recognition," 2008 International Conference on Machine Learning and Cybernetics, Kunming, 2008, pp. 3823-3826.
[25]M. A. A. Sheikh, A. Kole and T. Maity, "Traffic sign detection and classification using color feature and neural network," 2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI), Kolkata, 2016, pp. 307-311.
[26]Abedin, P. Dhar, M. K. Hossenand and K. Deb, "Traffic sign detection and recognition using fuzzy segmentation approach and artificial neural network classifier respectively," 2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), Cox's Bazar, 2017, pp. 518-523.
[27]V. Ngoc Hanh and D. Park, "Traffic Sign Detection with Color Probability Map Using Artificial Neural Networks", International Journal of Applied Engineering Research, vol. 11, no. 21, pp. 10655-10658, 2016.
[28]Supreeth H. S. G and C. M. Patil, "An approach towards efficient detection and recognition of traffic signs in videos using neural networks," 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, 2016, pp. 456-459.
[29]S. Jung, U. Lee, J. Jung and D. H. Shim, "Real-time Traffic Sign Recognition system with deep convolutional neural network," 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), Xi'an, 2016, pp. 31-34.
[30]S. C. Huang, H. Y. Lin and C. C. Chang, "An in-car camera system for traffic sign detection and recognition," 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS), Otsu, 2017, pp. 1-6.
[31]P.Uršič, D. Tabernik, R. Mandeljc and D. Skočaj, "Towards large-scale traffic sign detection and recognition", in 22nd Computer Vision Winter Workshop, Retz, Austria, 2017.
[32]Z. Chen, X. Huang, Z. Ni and H. He, "A GPU-based real-time traffic sign detection and recognition system," 2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS), Orlando, FL, 2014, pp.1-5.
[33]Y. Ma and L. Huang, "Hierarchical Traffic Sign Recognition Based on Multi-feature and Multi-classifier Fusion", Proceedings of the First International Conference on Information Science and Electronic Technology, 2015.
[34]A. Ellahyani, M. Ansari, I. Jaafari and S. Charfi, "Traffic Sign Detection and Recognition using Features Combination and Random Forests", International Journal of Advanced Computer Science and Applications, vol. 7, no. 1, pp. 686-693, 2016.
[35]K.Lim, H. Byun and Y. Choi, "A Real-time Traffic Sign Recognition System Based on Local Structure Features", in The 19th International Conference on Image Processing, Computer Vision, & Pattern Recognition, 2015, pp. 65-68.
[36]J. H. Shi and H. Y. Lin, "A vision system for traffic sign detection and recognition," 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE), Edinburgh, 2017, pp. 1596-1601.
[37]F. Zaklouta and B. Stanciulescu, "Real-time traffic sign recognition in three stages", Robotics and Autonomous Systems, vol. 62, no. 1, pp. 16-24, 2014..
[38]H. Thanh, "Morphological Classification for Traffic Sign Recognition", Electrical and Electronic Engineering, vol. 4, no. 2, pp. 36-44., 2014.
[39]L. Chen, Q. Li, M. Li and Q. Mao, "Traffic sign detection and recognition for intelligent vehicle," 2011 IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, 2011, pp. 908-913.
[40]H. N. Dean and K. V. Jabir, “Real Time Detection and Recognition of Indian Traffic Signs using Matlab”, International Journal of Scientific & Engineering Research, Volume 4, Issue 5, pp. 684-690, 2013.
[41]M. Kobayashi, M. Baba, K. Ohtani and L. Li, "A method for traffic sign detection and recognition based on genetic algorithm," 2015 IEEE/SICE International Symposium on System Integration (SII), Nagoya, 2015, pp. 455-460.
[42]X. Baro, S. Escalera, J. Vitria, O. Pujol and P. Radeva, "Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification," in IEEE Transactions on Intelligent Transportation Systems, vol. 10, no. 1, pp. 113-126, March 2009.
[43]M. Billah, S. Waheed, K. Ahmed and A. Hanifa, "Real Time Traffic Sign Detection and Recognition using Adaptive Neuro Fuzzy Inference System", Communications on Applied Electronics, vol. 3, no. 2, pp. 1-5, 2015.
[44]Soetedjo A., Yamada K. "Fast and robust traffic sign detection", Systems, man and cybernetics, vol. 2, pp. 1341-1346, 2005.
[45]Soetedjo A., Yamada K, "An efficient algorithm for traffic sign detection", Journal of advanced computational intelligence and intelligent informatics, vol. 10, no 3, pp. 409-418, 2005.
[46]S. Marsi et al., “Video Enhancement and Dynamic Range Control of HDR Sequences for Automotive Applications ” EURASIP J. Advances in Signal Processing, vol. 2007, 2007, p. 9.
[47]M. García Garrido, M. Sotelo and E. Martm-Gorostiza, "Fast Traffic Sign Detection and Recognition Under Changing Lighting Conditions", in 2006 IEEE Intelligent Transportation Systems Conference, Toronto, Canada, 2006, pp. 811-816.
[48]W. J. Kuo and C. C. Lin, "Two-Stage Road Sign Detection and Recognition," 2007 IEEE International Conference on Multimedia and Expo, Beijing, 2007, pp. 1427-1430.
[49]S. Ren, K. He, R. B. Girshick, and J. Sun, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks,” in NIPS, 2015, pp. 91–99.
[50]E. Oruklu, D. Pesty, J. Neveux and J. E. Guebey, "Real-time traffic sign detection and recognition for in-car driver assistance systems," 2012 IEEE 55th International Midwest Symposium on Circuits and Systems (MWSCAS), Boise, ID, 2012, pp. 976-979.
[51]Z. Zheng, H. Zhang, B. Wang, and Z. Gao, “Robust traffic sign recognition and tracking for Advanced Driver Assistance. Systems,” 15th International IEEE Conference on Intelligent Transportation Systems (ITSC), 2012, pp. 704–709.
[52]Z . Omary and F. Mtenzi, "Machine learning approach to identifying the dataset threshold for the performance estimators in supervised learning," International Journal for Infonomics (IJI), vol. 3, Sept. 2010, p:314–325.
[53]R. Michalski, J. Carbonell, and T. Mitchell, Machine Learning: An Artificial Intelligence Approach. Morgan Kaufmann, 1986.
[54]S. Vitabile, A. Gentile, and F. Sorbello, "A neural network based automatic road sign recognizer," presented at The 2002 Inter. Joint Conf. on Neural Networks, Honolulu, HI, USA, 2002.
[55]J. Miura, T. Kanda, and Y. Shirai, "An active vision system for real-time traffic sign recognition," presented at 2000 IEEE Intelligent Transportation Systems, Dearborn, MI, USA, 2000.
[56]S. Vitabile, A. Gentile, G. Dammone, and F. Sorbello, "Multi-layer perceptron mapping on a SIMD architecture," presented at The 2002 IEEE Signal Processing Society Workshop, 2002.
[57]Bangladesh Road Transport Authority, "BANGLADESH ROAD SIGN MANUAL", Bangladesh Road Transport Authority. Available: http://www.rhd.gov.bd/Documents/ConvDocs/Road%20Sign%20Manual%20Volume-1.pdf [Accessed: 12- Dec- 2017]
[58]H. Cheng, X. Jiang, Y. Sun and J. Wang, "Color image segmentation: advances and prospects", Pattern Recognition, vol. 34, no. 12, pp. 2259-2281, 2001.
[59]H. Fleyeh, "Traffic and Road Sign Recognition", Ph.D., Napier University, 2008.
[60]A. Ruta, Y. Li, and X. Liu, “Real-Time Traffic Sign Recognition from Video by Class-Specific Discriminative Features,” Pattern Recognition, vol. 43, no. 1, 2010, pp. 416–30.
[61]"ADAC: BMW has best traffic-sign recognition", automotiveIT International, 2010 [Online]. Available: http://www.automotiveit.com/news/adac-bmw-has-best-traffic-sign-recognition/. [Accessed: 23- Jan- 2018]
[62]J. Levinson et al., "Towards fully autonomous driving: Systems and algorithms," 2011 IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, 2011, pp. 163-168.
[63]J. Markoff, "Google Cars Drive Themselves, in Traffic", The New Work Times, 2010.
[64]Geonovum, "Self-Driving Vehicles & Geo-Information", Geonovum [Online]. Available: https://www.geonovum.nl/sites/default/files/Self-DrivingVehiclesReport.pdf. [Accessed: 21- Feb- 2018]
[65]Michalski, Ryszard S., Carbonell, Jamie G. and Mitchell, Tom. M. Machine learning: An Artificial Intelligence Approach. Morgan Kaufmann, 1985.
[66]H. Bay, A. Ess, T. Tuytelaars, and L. V. Gool, "SURF: Speeded up robust features," Computer Vision and Image Understanding, vol. 110, no. 3, pp. 346–359, 2008
[67]D. Lowe, “Distinctive image features from scale-invariant key points, “International Journal of Computer Vision, vol. 60, no. 2, pp. 91–110, November 2004.
[68]L. Auria and R. Moro, "Support Vector Machines (SVM) as a Technique for Solvency Analysis", SSRN Electronic Journal, 2008.
[69]"Convolutional Neural Networks - Convolutional Neural Networks for Image and Video Processing - TUM Wiki", Wiki.tum.de, 2018. [Online]. Available: https://wiki.tum.de/display/lfdv/Convolutional+Neural+Networks. [Accessed: 27- Feb- 2018]
[70]M. O. Rahman, F. A. Mousumi, E. Scavino, A. Hussain and H. Basri, "Real time road sign recognition system using artificial neural networks for bengali textual information box," 2008 International Symposium on Information Technology, Kuala Lumpur, Malaysia, 2008, pp. 1-8
[71]R. Gonzalez and R. Woods, Digital image processing. Upper Saddle River, N.J.: Prentice Hall, 2002.
[72]Y. Freund and R. E. Schapire, "Experiments with a new boosting algorithm," in International Conference on Machine Learning, 1996, pp. 148–156.